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1,109 | llm | https://github.com/juncongmoo/pyllama | [] | null | [] | ['pyllama'] | null | null | Start 2023-04-13 | juncongmoo/pyllama | pyllama | 2,732 | 309 | 36 | Python | null | LLaMA: Open and Efficient Foundation Language Models | juncongmoo | 2024-01-14 | 2023-02-28 | 48 | 56.916667 | null | LLaMA: Open and Efficient Foundation Language Models | [] | [] | 2023-04-25 | [('ai21labs/lm-evaluation', 0.699636697769165, 'llm', 0), ('hannibal046/awesome-llm', 0.6920731067657471, 'study', 0), ('optimalscale/lmflow', 0.6721161007881165, 'llm', 0), ('cg123/mergekit', 0.6644551753997803, 'llm', 0), ('freedomintelligence/llmzoo', 0.6618118286132812, 'llm', 0), ('ctlllll/llm-toolmaker', 0.650133... | 11 | 3 | null | 0.83 | 7 | 2 | 11 | 9 | 1 | 1 | 1 | 7 | 7 | 90 | 1 | 48 |
677 | util | https://github.com/spotify/basic-pitch | [] | null | [] | [] | null | null | null | spotify/basic-pitch | basic-pitch | 2,654 | 186 | 48 | Python | https://basicpitch.io | A lightweight yet powerful audio-to-MIDI converter with pitch bend detection | spotify | 2024-01-14 | 2022-05-03 | 91 | 29.164835 | https://avatars.githubusercontent.com/u/251374?v=4 | A lightweight yet powerful audio-to-MIDI converter with pitch bend detection | ['audio', 'lightweight', 'machine-learning', 'midi', 'music', 'pitch-detection', 'polyphonic', 'transcription', 'typescript'] | ['audio', 'lightweight', 'machine-learning', 'midi', 'music', 'pitch-detection', 'polyphonic', 'transcription', 'typescript'] | 2023-09-12 | [('espnet/espnet', 0.5158132910728455, 'nlp', 0), ('facebookresearch/audiocraft', 0.5119118094444275, 'util', 1)] | 17 | 4 | null | 0.67 | 14 | 5 | 21 | 4 | 3 | 2 | 3 | 14 | 18 | 90 | 1.3 | 48 |
850 | jupyter | https://github.com/jupyter/nbdime | [] | null | [] | [] | null | null | null | jupyter/nbdime | nbdime | 2,562 | 164 | 42 | TypeScript | http://nbdime.readthedocs.io | Tools for diffing and merging of Jupyter notebooks. | jupyter | 2024-01-13 | 2015-11-16 | 428 | 5.983984 | https://avatars.githubusercontent.com/u/7388996?v=4 | Tools for diffing and merging of Jupyter notebooks. | ['diff', 'diffing', 'git', 'hg', 'jupyter', 'jupyter-notebook', 'jupyterlab-extension', 'mercurial', 'merge', 'merge-driver', 'mergetool', 'vcs', 'version-control'] | ['diff', 'diffing', 'git', 'hg', 'jupyter', 'jupyter-notebook', 'jupyterlab-extension', 'mercurial', 'merge', 'merge-driver', 'mergetool', 'vcs', 'version-control'] | 2023-11-21 | [('mwouts/jupytext', 0.6408078074455261, 'jupyter', 3), ('jupyter/nbformat', 0.6054288148880005, 'jupyter', 0), ('quantopian/qgrid', 0.5866443514823914, 'jupyter', 0), ('voila-dashboards/voila', 0.5848777890205383, 'jupyter', 3), ('jupyter-widgets/ipywidgets', 0.5793547034263611, 'jupyter', 1), ('jupyter/nbconvert', 0.... | 50 | 5 | null | 2.46 | 47 | 36 | 99 | 2 | 6 | 11 | 6 | 47 | 182 | 90 | 3.9 | 48 |
1,159 | util | https://github.com/whylabs/whylogs | [] | null | [] | [] | null | null | null | whylabs/whylogs | whylogs | 2,444 | 109 | 32 | Jupyter Notebook | https://whylogs.readthedocs.io/ | An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈 | whylabs | 2024-01-13 | 2020-08-14 | 180 | 13.53481 | https://avatars.githubusercontent.com/u/56651354?v=4 | An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈 | ['ai-pipelines', 'analytics', 'approximate-statistics', 'calculate-statistics', 'constraints', 'data-constraints', 'data-pipeline', 'data-quality', 'data-science', 'dataops', 'dataset', 'logging', 'machine-learning', 'ml-pipelines', 'mlops', 'model-performance', 'statistical-properties'] | ['ai-pipelines', 'analytics', 'approximate-statistics', 'calculate-statistics', 'constraints', 'data-constraints', 'data-pipeline', 'data-quality', 'data-science', 'dataops', 'dataset', 'logging', 'machine-learning', 'ml-pipelines', 'mlops', 'model-performance', 'statistical-properties'] | 2024-01-11 | [('salesforce/logai', 0.7454851269721985, 'util', 1), ('polyaxon/datatile', 0.5969440937042236, 'pandas', 4), ('wandb/client', 0.5798064470291138, 'ml', 3), ('aimhubio/aim', 0.5764767527580261, 'ml-ops', 3), ('mlflow/mlflow', 0.5756088495254517, 'ml-ops', 1), ('cleanlab/cleanlab', 0.5660983324050903, 'ml', 3), ('netfli... | 23 | 3 | null | 5.04 | 64 | 57 | 42 | 0 | 54 | 43 | 54 | 64 | 16 | 90 | 0.2 | 48 |
914 | profiling | https://github.com/pyutils/line_profiler | [] | null | [] | [] | null | null | null | pyutils/line_profiler | line_profiler | 2,304 | 112 | 14 | Python | null | Line-by-line profiling for Python | pyutils | 2024-01-14 | 2019-12-10 | 216 | 10.666667 | https://avatars.githubusercontent.com/u/58752944?v=4 | Line-by-line profiling for Python | [] | [] | 2023-12-05 | [('benfred/py-spy', 0.6891393065452576, 'profiling', 0), ('pythonspeed/filprofiler', 0.6149646043777466, 'profiling', 0), ('landscapeio/prospector', 0.5992322564125061, 'util', 0), ('gaogaotiantian/viztracer', 0.5905494689941406, 'profiling', 0), ('pympler/pympler', 0.5873364806175232, 'perf', 0), ('klen/py-frameworks-... | 43 | 5 | null | 2.12 | 20 | 13 | 50 | 1 | 4 | 5 | 4 | 20 | 44 | 90 | 2.2 | 48 |
1,073 | ml | https://github.com/google-research/t5x | [] | null | [] | [] | null | null | null | google-research/t5x | t5x | 2,278 | 275 | 36 | Python | null | null | google-research | 2024-01-13 | 2021-11-01 | 117 | 19.446341 | https://avatars.githubusercontent.com/u/43830688?v=4 | google-research/t5x | [] | [] | 2024-01-13 | [('google-research/byt5', 0.8195183277130127, 'nlp', 0), ('google-research/google-research', 0.6067818999290466, 'ml', 0)] | 106 | 3 | null | 4.54 | 81 | 45 | 27 | 0 | 0 | 0 | 0 | 81 | 25 | 90 | 0.3 | 48 |
1,395 | llm | https://github.com/civitai/sd_civitai_extension | [] | null | [] | [] | null | null | null | civitai/sd_civitai_extension | sd_civitai_extension | 2,139 | 405 | 73 | Python | null | All of the Civitai models inside Automatic 1111 Stable Diffusion Web UI | civitai | 2024-01-14 | 2022-12-06 | 60 | 35.65 | https://avatars.githubusercontent.com/u/117393426?v=4 | All of the Civitai models inside Automatic 1111 Stable Diffusion Web UI | [] | [] | 2023-12-21 | [('mlc-ai/web-stable-diffusion', 0.6748091578483582, 'diffusion', 0), ('automatic1111/stable-diffusion-webui', 0.6364338397979736, 'diffusion', 0), ('thereforegames/unprompted', 0.6360564827919006, 'diffusion', 0), ('comfyanonymous/comfyui', 0.6050902009010315, 'diffusion', 0), ('carson-katri/dream-textures', 0.5569747... | 10 | 5 | null | 1 | 24 | 3 | 13 | 1 | 0 | 0 | 0 | 24 | 20 | 90 | 0.8 | 48 |
1,327 | llm | https://github.com/young-geng/easylm | [] | null | [] | [] | null | null | null | young-geng/easylm | EasyLM | 2,093 | 209 | 36 | Python | null | Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax. | young-geng | 2024-01-13 | 2022-11-22 | 62 | 33.758065 | null | Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax. | ['chatbot', 'deep-learning', 'flax', 'jax', 'language-model', 'large-language-models', 'llama', 'natural-language-processing', 'transformer'] | ['chatbot', 'deep-learning', 'flax', 'jax', 'language-model', 'large-language-models', 'llama', 'natural-language-processing', 'transformer'] | 2023-08-31 | [('hiyouga/llama-factory', 0.6924945116043091, 'llm', 3), ('hiyouga/llama-efficient-tuning', 0.6924943923950195, 'llm', 3), ('nomic-ai/gpt4all', 0.6724932789802551, 'llm', 2), ('salesforce/xgen', 0.6715541481971741, 'llm', 2), ('bigscience-workshop/petals', 0.6689819693565369, 'data', 5), ('deepset-ai/haystack', 0.6550... | 11 | 6 | null | 2.85 | 10 | 2 | 14 | 5 | 0 | 0 | 0 | 10 | 14 | 90 | 1.4 | 48 |
799 | web | https://github.com/python-restx/flask-restx | [] | null | [] | [] | null | null | null | python-restx/flask-restx | flask-restx | 2,020 | 326 | 66 | Python | https://flask-restx.readthedocs.io/en/latest/ | Fork of Flask-RESTPlus: Fully featured framework for fast, easy and documented API development with Flask | python-restx | 2024-01-13 | 2020-01-09 | 211 | 9.541161 | https://avatars.githubusercontent.com/u/59693083?v=4 | Fork of Flask-RESTPlus: Fully featured framework for fast, easy and documented API development with Flask | ['api', 'flask', 'json', 'rest', 'restful', 'restplus', 'restx', 'swagger'] | ['api', 'flask', 'json', 'rest', 'restful', 'restplus', 'restx', 'swagger'] | 2023-12-10 | [('pyeve/eve', 0.7703225612640381, 'web', 2), ('vitalik/django-ninja', 0.7110880613327026, 'web', 1), ('tiangolo/fastapi', 0.6711971163749695, 'web', 4), ('starlite-api/starlite', 0.6593479514122009, 'web', 3), ('pallets/flask', 0.6463286280632019, 'web', 1), ('falconry/falcon', 0.6462195515632629, 'web', 2), ('bottlep... | 147 | 7 | null | 0.56 | 34 | 18 | 49 | 1 | 4 | 4 | 4 | 34 | 47 | 90 | 1.4 | 48 |
1,758 | ml | https://github.com/rom1504/clip-retrieval | [] | null | [] | [] | null | null | null | rom1504/clip-retrieval | clip-retrieval | 1,917 | 181 | 22 | Jupyter Notebook | https://rom1504.github.io/clip-retrieval/ | Easily compute clip embeddings and build a clip retrieval system with them | rom1504 | 2024-01-14 | 2021-06-07 | 138 | 13.876939 | null | Easily compute clip embeddings and build a clip retrieval system with them | ['ai', 'clip', 'deep-learning', 'knn', 'multimodal', 'semantic-search'] | ['ai', 'clip', 'deep-learning', 'knn', 'multimodal', 'semantic-search'] | 2024-01-13 | [('jina-ai/clip-as-service', 0.6420944929122925, 'nlp', 1), ('openai/clip', 0.5981614589691162, 'ml-dl', 2), ('albumentations-team/albumentations', 0.5307724475860596, 'ml-dl', 1), ('nomic-ai/nomic', 0.5256919264793396, 'nlp', 0), ('chroma-core/chroma', 0.5229653716087341, 'data', 0), ('qdrant/fastembed', 0.51383501291... | 26 | 3 | null | 1.08 | 123 | 69 | 32 | 0 | 9 | 33 | 9 | 123 | 80 | 90 | 0.7 | 48 |
1,050 | util | https://github.com/home-assistant/supervisor | [] | null | [] | [] | null | null | null | home-assistant/supervisor | supervisor | 1,559 | 553 | 85 | Python | https://home-assistant.io/hassio/ | :house_with_garden: Home Assistant Supervisor | home-assistant | 2024-01-12 | 2017-03-14 | 359 | 4.342618 | https://avatars.githubusercontent.com/u/13844975?v=4 | 🏡 Home Assistant Supervisor | ['docker', 'home-assistant', 'home-automation', 'orchestrator'] | ['docker', 'home-assistant', 'home-automation', 'orchestrator'] | 2024-01-13 | [('prefecthq/server', 0.5141927599906921, 'util', 0)] | 76 | 3 | null | 8.54 | 239 | 205 | 83 | 0 | 37 | 61 | 37 | 239 | 452 | 90 | 1.9 | 48 |
714 | math | https://github.com/facebookresearch/theseus | [] | null | [] | [] | null | null | null | facebookresearch/theseus | theseus | 1,523 | 116 | 29 | Python | null | A library for differentiable nonlinear optimization | facebookresearch | 2024-01-12 | 2021-11-18 | 114 | 13.276463 | https://avatars.githubusercontent.com/u/16943930?v=4 | A library for differentiable nonlinear optimization | ['bilevel-optimization', 'computer-vision', 'deep-learning', 'differentiable-optimization', 'embodied-ai', 'gauss-newton', 'implicit-differentiation', 'levenberg-marquardt', 'nonlinear-least-squares', 'pytorch', 'robotics'] | ['bilevel-optimization', 'computer-vision', 'deep-learning', 'differentiable-optimization', 'embodied-ai', 'gauss-newton', 'implicit-differentiation', 'levenberg-marquardt', 'nonlinear-least-squares', 'pytorch', 'robotics'] | 2023-12-22 | [('tensorlayer/tensorlayer', 0.553860068321228, 'ml-rl', 1), ('pytorch/rl', 0.5316617488861084, 'ml-rl', 2), ('explosion/thinc', 0.5256298184394836, 'ml-dl', 2), ('thu-ml/tianshou', 0.5228813886642456, 'ml-rl', 1), ('pytorch/ignite', 0.5099302530288696, 'ml-dl', 2), ('tensorflow/tensor2tensor', 0.5072576403617859, 'ml'... | 25 | 4 | null | 2 | 24 | 17 | 26 | 1 | 3 | 5 | 3 | 24 | 67 | 90 | 2.8 | 48 |
632 | perf | https://github.com/dask/distributed | [] | null | [] | [] | null | null | null | dask/distributed | distributed | 1,513 | 706 | 56 | Python | https://distributed.dask.org | A distributed task scheduler for Dask | dask | 2024-01-13 | 2015-09-13 | 437 | 3.45998 | https://avatars.githubusercontent.com/u/17131925?v=4 | A distributed task scheduler for Dask | ['dask', 'distributed-computing', 'pydata'] | ['dask', 'distributed-computing', 'pydata'] | 2024-01-12 | [('dask/dask', 0.719694972038269, 'perf', 2), ('prefecthq/prefect-dask', 0.6549785137176514, 'util', 1), ('agronholm/apscheduler', 0.5948215126991272, 'util', 0), ('fugue-project/fugue', 0.5652367472648621, 'pandas', 2), ('dask/dask-ml', 0.5617966055870056, 'ml', 0), ('backtick-se/cowait', 0.56135493516922, 'util', 1),... | 322 | 2 | null | 10.19 | 243 | 164 | 101 | 0 | 0 | 26 | 26 | 242 | 567 | 90 | 2.3 | 48 |
1,652 | llm | https://github.com/farizrahman4u/loopgpt | [] | Re-implementation of Auto-GPT as a python package, written with modularity and extensibility in mind. | [] | [] | null | null | null | farizrahman4u/loopgpt | loopgpt | 1,339 | 128 | 34 | Python | null | Modular Auto-GPT Framework | farizrahman4u | 2024-01-12 | 2023-04-14 | 41 | 32.209622 | null | Modular Auto-GPT Framework | ['chatgpt', 'gpt', 'gpt4', 'llms'] | ['chatgpt', 'gpt', 'gpt4', 'llms'] | 2023-10-20 | [('mmabrouk/chatgpt-wrapper', 0.6415730118751526, 'llm', 2), ('xtekky/gpt4free', 0.617682158946991, 'llm', 3), ('instruction-tuning-with-gpt-4/gpt-4-llm', 0.5821303129196167, 'llm', 1), ('microsoft/autogen', 0.5695356726646423, 'llm', 2), ('killianlucas/open-interpreter', 0.5448848605155945, 'llm', 1), ('eth-sri/lmql',... | 12 | 4 | null | 5.17 | 1 | 0 | 9 | 3 | 7 | 9 | 7 | 1 | 1 | 90 | 1 | 48 |
1,241 | ml | https://github.com/visual-layer/fastdup | [] | null | [] | [] | null | null | null | visual-layer/fastdup | fastdup | 1,302 | 67 | 20 | Python | null | fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale. | visual-layer | 2024-01-12 | 2022-05-11 | 89 | 14.489666 | https://avatars.githubusercontent.com/u/116299338?v=4 | fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale. | ['data-augmentation', 'data-curation', 'dataset', 'deep-learning', 'image', 'image-analysis', 'image-classfication', 'image-classification', 'image-duplicate-detection', 'image-processing', 'image-similarity', 'machine-learning', 'novelty-detection', 'object-detection', 'outlier-detection', 'visual-search', 'visualizat... | ['data-augmentation', 'data-curation', 'dataset', 'deep-learning', 'image', 'image-analysis', 'image-classfication', 'image-classification', 'image-duplicate-detection', 'image-processing', 'image-similarity', 'machine-learning', 'novelty-detection', 'object-detection', 'outlier-detection', 'visual-search', 'visualizat... | 2024-01-09 | [('albumentations-team/albumentations', 0.5445998311042786, 'ml-dl', 5), ('towhee-io/towhee', 0.5181317925453186, 'ml-ops', 2), ('huggingface/datasets', 0.5084423422813416, 'nlp', 2)] | 20 | 1 | null | 12.88 | 28 | 18 | 20 | 0 | 61 | 83 | 61 | 28 | 31 | 90 | 1.1 | 48 |
971 | ml | https://github.com/google/vizier | [] | null | [] | [] | null | null | null | google/vizier | vizier | 1,138 | 71 | 20 | Python | https://oss-vizier.readthedocs.io | Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service. | google | 2024-01-14 | 2022-02-16 | 101 | 11.172511 | https://avatars.githubusercontent.com/u/1342004?v=4 | Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service. | ['algorithm', 'bayesian-optimization', 'blackbox-optimization', 'deep-learning', 'distributed-computing', 'distributed-systems', 'evolutionary-algorithms', 'google', 'grpc', 'hyperparameter-optimization', 'hyperparameter-tuning', 'machine-learning', 'open-source', 'optimization', 'tuning', 'tuning-parameters', 'vizier'... | ['algorithm', 'bayesian-optimization', 'blackbox-optimization', 'deep-learning', 'distributed-computing', 'distributed-systems', 'evolutionary-algorithms', 'google', 'grpc', 'hyperparameter-optimization', 'hyperparameter-tuning', 'machine-learning', 'open-source', 'optimization', 'tuning', 'tuning-parameters', 'vizier'... | 2024-01-12 | [('scikit-optimize/scikit-optimize', 0.6410875916481018, 'ml', 5), ('determined-ai/determined', 0.6237358450889587, 'ml-ops', 4), ('epistasislab/tpot', 0.6137571930885315, 'ml', 2), ('microsoft/nni', 0.5949028134346008, 'ml', 5), ('ray-project/ray', 0.5806607604026794, 'ml-ops', 4), ('hyperopt/hyperopt', 0.575022399425... | 21 | 4 | null | 9.52 | 99 | 94 | 23 | 0 | 15 | 17 | 15 | 99 | 25 | 90 | 0.3 | 48 |
1,573 | data | https://github.com/pathwaycom/pathway | ['llmops'] | null | [] | [] | null | null | null | pathwaycom/pathway | pathway | 1,079 | 42 | 18 | Python | https://pathway.com | Pathway is a high-throughput, low-latency data processing framework that handles live data & streaming for you. Made with ❤️ for Python & ML/AI developers. | pathwaycom | 2024-01-13 | 2022-11-27 | 61 | 17.606061 | https://avatars.githubusercontent.com/u/25750857?v=4 | Pathway is a high-throughput, low-latency data processing framework that handles live data & streaming for you. Made with ❤️ for Python & ML/AI developers. | ['batch-processing', 'kafka', 'machine-learning-algorithms', 'pathway', 'real-time', 'streaming'] | ['batch-processing', 'kafka', 'llmops', 'machine-learning-algorithms', 'pathway', 'real-time', 'streaming'] | 2024-01-12 | [('airtai/faststream', 0.6327610611915588, 'perf', 1), ('google/mediapipe', 0.5712288022041321, 'ml', 0), ('mage-ai/mage-ai', 0.5671728849411011, 'ml-ops', 0), ('activeloopai/deeplake', 0.5419109463691711, 'ml-ops', 0), ('online-ml/river', 0.5360531210899353, 'ml', 1), ('dagworks-inc/hamilton', 0.5315225720405579, 'ml-... | 13 | 5 | null | 1 | 1 | 1 | 14 | 0 | 22 | 19 | 22 | 1 | 2 | 90 | 2 | 48 |
1,895 | time-series | https://github.com/google/temporian | ['feature-engineering', 'temporal-data'] | null | [] | [] | 1 | null | null | google/temporian | temporian | 445 | 28 | 11 | Python | https://temporian.readthedocs.io | Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖 | google | 2024-01-12 | 2023-01-17 | 54 | 8.240741 | https://avatars.githubusercontent.com/u/1342004?v=4 | Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖 | ['cpp', 'feature-engineering', 'temporal-data', 'time-series'] | ['cpp', 'feature-engineering', 'temporal-data', 'time-series'] | 2024-01-12 | [('featurelabs/featuretools', 0.7070109844207764, 'ml', 1), ('pycaret/pycaret', 0.6051017045974731, 'ml', 1), ('firmai/atspy', 0.6023882031440735, 'time-series', 1), ('rasbt/mlxtend', 0.58907151222229, 'ml', 0), ('alkaline-ml/pmdarima', 0.5879765152931213, 'time-series', 1), ('gradio-app/gradio', 0.5871459245681763, 'v... | 12 | 3 | null | 36.23 | 60 | 56 | 12 | 0 | 7 | 9 | 7 | 60 | 122 | 90 | 2 | 48 |
491 | ml-dl | https://github.com/rasbt/deeplearning-models | [] | null | [] | [] | null | null | null | rasbt/deeplearning-models | deeplearning-models | 16,133 | 3,949 | 599 | Jupyter Notebook | null | A collection of various deep learning architectures, models, and tips | rasbt | 2024-01-14 | 2019-06-05 | 242 | 66.43 | null | A collection of various deep learning architectures, models, and tips | [] | [] | 2023-02-16 | [('pytorch/ignite', 0.5799865126609802, 'ml-dl', 0), ('tensorflow/tensor2tensor', 0.5731253623962402, 'ml', 0), ('tensorflow/tensorflow', 0.5665931105613708, 'ml-dl', 0), ('christoschristofidis/awesome-deep-learning', 0.5625115036964417, 'study', 0), ('mrdbourke/pytorch-deep-learning', 0.5607303977012634, 'study', 0), ... | 13 | 6 | null | 0.08 | 0 | 0 | 56 | 11 | 0 | 0 | 0 | 0 | 0 | 90 | 0 | 47 |
24 | ml-rl | https://github.com/google/dopamine | [] | null | [] | [] | null | null | null | google/dopamine | dopamine | 10,288 | 1,410 | 435 | Jupyter Notebook | https://github.com/google/dopamine | Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. | google | 2024-01-11 | 2018-07-26 | 287 | 35.757696 | https://avatars.githubusercontent.com/u/1342004?v=4 | Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. | ['ai', 'google', 'ml', 'rl', 'tensorflow'] | ['ai', 'google', 'ml', 'rl', 'tensorflow'] | 2023-11-27 | [('pytorch/rl', 0.6595585942268372, 'ml-rl', 2), ('unity-technologies/ml-agents', 0.6415248513221741, 'ml-rl', 0), ('thu-ml/tianshou', 0.6199951171875, 'ml-rl', 1), ('tensorlayer/tensorlayer', 0.5985347628593445, 'ml-rl', 2), ('keras-rl/keras-rl', 0.5969773530960083, 'ml-rl', 1), ('farama-foundation/gymnasium', 0.58465... | 15 | 4 | null | 0.19 | 5 | 2 | 67 | 2 | 0 | 0 | 0 | 5 | 3 | 90 | 0.6 | 47 |
1,107 | ml | https://github.com/twitter/the-algorithm-ml | [] | null | [] | [] | null | null | null | twitter/the-algorithm-ml | the-algorithm-ml | 9,797 | 2,242 | 100 | Python | https://blog.twitter.com/engineering/en_us/topics/open-source/2023/twitter-recommendation-algorithm | Source code for Twitter's Recommendation Algorithm | twitter | 2024-01-13 | 2023-03-27 | 44 | 221.938511 | https://avatars.githubusercontent.com/u/50278?v=4 | Source code for Twitter's Recommendation Algorithm | [] | [] | 2023-04-06 | [] | 0 | -1 | 23 | 1 | 2 | 2 | 10 | 9 | 0 | 0 | 0 | 2 | 0 | 90 | 0 | 47 |
996 | finance | https://github.com/ta-lib/ta-lib-python | [] | null | [] | [] | null | null | null | ta-lib/ta-lib-python | ta-lib-python | 8,658 | 1,703 | 325 | Cython | http://ta-lib.github.io/ta-lib-python | Python wrapper for TA-Lib (http://ta-lib.org/). | ta-lib | 2024-01-14 | 2012-03-23 | 618 | 13.996767 | https://avatars.githubusercontent.com/u/21127168?v=4 | Python wrapper for TA-Lib (http://ta-lib.org/). | ['finance', 'pattern-recognition', 'quantitative-finance', 'ta-lib', 'technical-analysis'] | ['finance', 'pattern-recognition', 'quantitative-finance', 'ta-lib', 'technical-analysis'] | 2023-12-30 | [('goldmansachs/gs-quant', 0.6905857920646667, 'finance', 0), ('pytoolz/toolz', 0.653429388999939, 'util', 0), ('cuemacro/finmarketpy', 0.6374157071113586, 'finance', 0), ('twopirllc/pandas-ta', 0.6217855215072632, 'finance', 2), ('alkaline-ml/pmdarima', 0.6164563894271851, 'time-series', 0), ('rasbt/mlxtend', 0.599006... | 29 | 1 | null | 0.58 | 25 | 10 | 144 | 0 | 0 | 2 | 2 | 25 | 47 | 90 | 1.9 | 47 |
838 | time-series | https://github.com/blue-yonder/tsfresh | [] | null | [] | [] | null | null | null | blue-yonder/tsfresh | tsfresh | 7,953 | 1,199 | 167 | Jupyter Notebook | http://tsfresh.readthedocs.io | Automatic extraction of relevant features from time series: | blue-yonder | 2024-01-13 | 2016-10-26 | 378 | 20.992081 | https://avatars.githubusercontent.com/u/6234170?v=4 | Automatic extraction of relevant features from time series: | ['data-science', 'feature-extraction', 'time-series'] | ['data-science', 'feature-extraction', 'time-series'] | 2023-10-24 | [('salesforce/merlion', 0.6107531189918518, 'time-series', 1), ('sktime/sktime', 0.5950053930282593, 'time-series', 2), ('tdameritrade/stumpy', 0.5777381062507629, 'time-series', 1), ('google/temporian', 0.5776029229164124, 'time-series', 1), ('alkaline-ml/pmdarima', 0.5346757173538208, 'time-series', 1), ('unit8co/dar... | 91 | 3 | null | 0.48 | 6 | 2 | 88 | 3 | 1 | 4 | 1 | 6 | 6 | 90 | 1 | 47 |
1,128 | ml | https://github.com/scikit-learn-contrib/imbalanced-learn | [] | null | [] | [] | null | null | null | scikit-learn-contrib/imbalanced-learn | imbalanced-learn | 6,603 | 1,274 | 140 | Python | https://imbalanced-learn.org | A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning | scikit-learn-contrib | 2024-01-12 | 2014-08-16 | 493 | 13.381876 | https://avatars.githubusercontent.com/u/17349883?v=4 | A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning | ['data-analysis', 'data-science', 'machine-learning', 'statistics'] | ['data-analysis', 'data-science', 'machine-learning', 'statistics'] | 2023-10-23 | [('pycaret/pycaret', 0.6684343814849854, 'ml', 2), ('scikit-learn/scikit-learn', 0.6626807451248169, 'ml', 4), ('rasbt/mlxtend', 0.651149570941925, 'ml', 2), ('yzhao062/pyod', 0.589371383190155, 'data', 3), ('facebookresearch/balance', 0.5837095379829407, 'ml', 0), ('jovianml/opendatasets', 0.5723727941513062, 'data', ... | 80 | 6 | null | 0.83 | 14 | 10 | 115 | 3 | 1 | 3 | 1 | 14 | 13 | 90 | 0.9 | 47 |
421 | util | https://github.com/tebelorg/rpa-python | [] | null | [] | [] | null | null | null | tebelorg/rpa-python | RPA-Python | 4,316 | 648 | 103 | Python | null | Python package for doing RPA | tebelorg | 2024-01-13 | 2019-03-30 | 252 | 17.097906 | https://avatars.githubusercontent.com/u/10379612?v=4 | Python package for doing RPA | ['cross-platform', 'opencv', 'rpa', 'sikuli', 'tagui', 'tesseract'] | ['cross-platform', 'opencv', 'rpa', 'sikuli', 'tagui', 'tesseract'] | 2023-12-24 | [('openai/openai-python', 0.5686379671096802, 'util', 0), ('earthlab/earthpy', 0.5264238715171814, 'gis', 0), ('pypy/pypy', 0.5048558115959167, 'util', 0), ('imageio/imageio', 0.502187967300415, 'util', 0)] | 4 | 2 | null | 0.44 | 25 | 23 | 58 | 1 | 2 | 11 | 2 | 25 | 79 | 90 | 3.2 | 47 |
1,800 | ml | https://github.com/nv-tlabs/get3d | ['generative-model', '3d'] | Generative Model of High Quality 3D Textured Shapes Learned from Images | [] | [] | null | null | null | nv-tlabs/get3d | GET3D | 4,002 | 364 | 142 | Python | null | null | nv-tlabs | 2024-01-13 | 2022-09-08 | 72 | 55.037328 | https://avatars.githubusercontent.com/u/49653101?v=4 | Generative Model of High Quality 3D Textured Shapes Learned from Images | [] | ['3d', 'generative-model'] | 2023-10-23 | [('openai/image-gpt', 0.5187845826148987, 'llm', 0), ('sharonzhou/long_stable_diffusion', 0.5064239501953125, 'diffusion', 0)] | 4 | 1 | null | 0.08 | 12 | 6 | 16 | 3 | 0 | 0 | 0 | 12 | 20 | 90 | 1.7 | 47 |
610 | testing | https://github.com/spulec/freezegun | [] | null | [] | [] | null | null | null | spulec/freezegun | freezegun | 3,890 | 267 | 34 | Python | null | Let your Python tests travel through time | spulec | 2024-01-12 | 2012-12-11 | 581 | 6.695353 | null | Let your Python tests travel through time | [] | [] | 2023-12-19 | [('pmorissette/bt', 0.5981432199478149, 'finance', 0), ('wolever/parameterized', 0.5846211314201355, 'testing', 0), ('sdispater/pendulum', 0.54648357629776, 'util', 0), ('ionelmc/pytest-benchmark', 0.5428466200828552, 'testing', 0), ('nedbat/coveragepy', 0.5298979878425598, 'testing', 0), ('arrow-py/arrow', 0.513056516... | 112 | 7 | null | 0.42 | 56 | 21 | 135 | 0 | 3 | 5 | 3 | 56 | 50 | 90 | 0.9 | 47 |
441 | gis | https://github.com/shapely/shapely | ['geometric-algorithms', 'geometry'] | null | [] | [] | 1 | null | null | shapely/shapely | shapely | 3,549 | 554 | 88 | Python | https://shapely.readthedocs.io/en/stable/ | Manipulation and analysis of geometric objects | shapely | 2024-01-12 | 2011-12-31 | 630 | 5.629504 | https://avatars.githubusercontent.com/u/59894073?v=4 | Manipulation and analysis of geometric objects | [] | ['geometric-algorithms', 'geometry'] | 2024-01-04 | [('benbovy/spherely', 0.873152494430542, 'gis', 2), ('scikit-geometry/scikit-geometry', 0.5902884602546692, 'gis', 2), ('google-deepmind/alphageometry', 0.5421801805496216, 'math', 1)] | 151 | 5 | null | 1.4 | 67 | 20 | 147 | 0 | 2 | 8 | 2 | 67 | 123 | 90 | 1.8 | 47 |
657 | util | https://github.com/zeromq/pyzmq | [] | null | [] | [] | null | null | null | zeromq/pyzmq | pyzmq | 3,498 | 666 | 103 | Python | http://zguide.zeromq.org/py:all | PyZMQ: Python bindings for zeromq | zeromq | 2024-01-13 | 2010-07-21 | 705 | 4.955677 | https://avatars.githubusercontent.com/u/109777?v=4 | PyZMQ: Python bindings for zeromq | ['cython', 'zeromq'] | ['cython', 'zeromq'] | 2024-01-04 | [('quantumlib/cirq', 0.5248025059700012, 'sim', 0), ('pyscf/pyscf', 0.5071917772293091, 'sim', 0)] | 196 | 5 | null | 2.38 | 23 | 17 | 164 | 0 | 0 | 6 | 6 | 23 | 37 | 90 | 1.6 | 47 |
249 | web | https://github.com/websocket-client/websocket-client | [] | null | [] | [] | null | null | null | websocket-client/websocket-client | websocket-client | 3,381 | 805 | 86 | Python | https://github.com/websocket-client/websocket-client | WebSocket client for Python | websocket-client | 2024-01-12 | 2010-12-28 | 683 | 4.95022 | https://avatars.githubusercontent.com/u/24536015?v=4 | WebSocket client for Python | ['rfc-6455', 'websocket', 'websocket-client', 'websockets', 'websockets-client'] | ['rfc-6455', 'websocket', 'websocket-client', 'websockets', 'websockets-client'] | 2024-01-12 | [('miguelgrinberg/python-socketio', 0.7025880217552185, 'util', 1), ('encode/httpx', 0.6006039381027222, 'web', 0), ('simple-salesforce/simple-salesforce', 0.5527551770210266, 'data', 0), ('bmoscon/cryptofeed', 0.5356486439704895, 'crypto', 2), ('aio-libs/aiohttp', 0.5178495049476624, 'web', 0), ('paramiko/paramiko', 0... | 221 | 5 | null | 1.31 | 23 | 15 | 159 | 0 | 10 | 6 | 10 | 23 | 28 | 90 | 1.2 | 47 |
94 | web | https://github.com/unbit/uwsgi | [] | null | [] | [] | null | null | null | unbit/uwsgi | uwsgi | 3,374 | 681 | 111 | C | http://projects.unbit.it/uwsgi | uWSGI application server container | unbit | 2024-01-13 | 2011-10-09 | 642 | 5.253114 | null | uWSGI application server container | [] | [] | 2023-12-26 | [] | 359 | 5 | null | 0.48 | 54 | 24 | 149 | 1 | 0 | 10 | 10 | 54 | 88 | 90 | 1.6 | 47 |
618 | util | https://github.com/more-itertools/more-itertools | [] | null | [] | [] | null | null | null | more-itertools/more-itertools | more-itertools | 3,314 | 266 | 40 | Python | https://more-itertools.rtfd.io | More routines for operating on iterables, beyond itertools | more-itertools | 2024-01-13 | 2012-04-26 | 613 | 5.399907 | https://avatars.githubusercontent.com/u/61018589?v=4 | More routines for operating on iterables, beyond itertools | [] | [] | 2024-01-12 | [('fluentpython/example-code-2e', 0.5874441862106323, 'study', 0)] | 114 | 5 | null | 3.12 | 41 | 33 | 143 | 0 | 6 | 4 | 6 | 41 | 42 | 90 | 1 | 47 |
1,499 | ml-rl | https://github.com/deepmind/acme | [] | null | [] | [] | 1 | null | null | deepmind/acme | acme | 3,302 | 410 | 83 | Python | null | A library of reinforcement learning components and agents | deepmind | 2024-01-12 | 2020-05-01 | 195 | 16.883857 | https://avatars.githubusercontent.com/u/8596759?v=4 | A library of reinforcement learning components and agents | ['agents', 'reinforcement-learning', 'research'] | ['agents', 'reinforcement-learning', 'research'] | 2024-01-03 | [('pytorch/rl', 0.6701556444168091, 'ml-rl', 1), ('shangtongzhang/reinforcement-learning-an-introduction', 0.6519054770469666, 'study', 1), ('openai/gym', 0.6127493381500244, 'ml-rl', 1), ('thu-ml/tianshou', 0.5823108553886414, 'ml-rl', 0), ('pettingzoo-team/pettingzoo', 0.578000545501709, 'ml-rl', 1), ('farama-foundat... | 84 | 3 | null | 0.6 | 9 | 2 | 45 | 0 | 0 | 3 | 3 | 9 | 6 | 90 | 0.7 | 47 |
718 | util | https://github.com/ashleve/lightning-hydra-template | [] | null | [] | [] | null | null | null | ashleve/lightning-hydra-template | lightning-hydra-template | 3,296 | 545 | 25 | Python | null | PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡ | ashleve | 2024-01-14 | 2020-11-04 | 168 | 19.519459 | null | PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡ | ['best-practices', 'config', 'deep-learning', 'hydra', 'mlops', 'project-structure', 'pytorch', 'pytorch-lightning', 'reproducibility', 'template'] | ['best-practices', 'config', 'deep-learning', 'hydra', 'mlops', 'project-structure', 'pytorch', 'pytorch-lightning', 'reproducibility', 'template'] | 2023-09-25 | [('pytorch/ignite', 0.6497684717178345, 'ml-dl', 2), ('intel/intel-extension-for-pytorch', 0.6405739188194275, 'perf', 2), ('determined-ai/determined', 0.6221935153007507, 'ml-ops', 3), ('rasbt/machine-learning-book', 0.619256317615509, 'study', 2), ('aws/sagemaker-python-sdk', 0.6082078814506531, 'ml', 1), ('mrdbourke... | 32 | 6 | null | 0.56 | 19 | 4 | 39 | 4 | 7 | 4 | 7 | 19 | 6 | 90 | 0.3 | 47 |
1,003 | finance | https://github.com/matplotlib/mplfinance | [] | null | [] | [] | null | null | null | matplotlib/mplfinance | mplfinance | 3,155 | 589 | 85 | Python | https://pypi.org/project/mplfinance/ | Financial Markets Data Visualization using Matplotlib | matplotlib | 2024-01-13 | 2019-12-05 | 216 | 14.558339 | https://avatars.githubusercontent.com/u/215947?v=4 | Financial Markets Data Visualization using Matplotlib | ['candlestick', 'candlestick-chart', 'candlestickchart', 'finance', 'intraday-data', 'market-data', 'matplotlib', 'mplfinance', 'ohlc', 'ohlc-chart', 'ohlc-data', 'ohlc-plot', 'ohlcv', 'trading-days'] | ['candlestick', 'candlestick-chart', 'candlestickchart', 'finance', 'intraday-data', 'market-data', 'matplotlib', 'mplfinance', 'ohlc', 'ohlc-chart', 'ohlc-data', 'ohlc-plot', 'ohlcv', 'trading-days'] | 2023-08-01 | [('mwaskom/seaborn', 0.6046485900878906, 'viz', 1), ('cuemacro/chartpy', 0.574644148349762, 'viz', 1), ('hydrosquall/tiingo-python', 0.5679528713226318, 'finance', 1), ('ranaroussi/yfinance', 0.5448886156082153, 'finance', 1), ('holoviz/hvplot', 0.5378217101097107, 'pandas', 0), ('matplotlib/matplotlib', 0.534671962261... | 48 | 7 | null | 0.98 | 17 | 8 | 50 | 6 | 1 | 3 | 1 | 17 | 41 | 90 | 2.4 | 47 |
474 | gis | https://github.com/holoviz/datashader | [] | null | [] | [] | 1 | null | null | holoviz/datashader | datashader | 3,127 | 366 | 91 | Python | http://datashader.org | Quickly and accurately render even the largest data. | holoviz | 2024-01-12 | 2015-12-23 | 422 | 7.394932 | https://avatars.githubusercontent.com/u/51678735?v=4 | Quickly and accurately render even the largest data. | ['data-visualizations', 'datashader', 'holoviz', 'rasterization'] | ['data-visualizations', 'datashader', 'holoviz', 'rasterization'] | 2024-01-08 | [('nomic-ai/deepscatter', 0.6156784296035767, 'viz', 0), ('pyqtgraph/pyqtgraph', 0.5956966876983643, 'viz', 0), ('holoviz/hvplot', 0.5903522372245789, 'pandas', 2), ('holoviz/holoviz', 0.5855922698974609, 'viz', 2), ('vaexio/vaex', 0.5661620497703552, 'perf', 0), ('man-group/dtale', 0.5459538698196411, 'viz', 0), ('vis... | 54 | 6 | null | 1.88 | 44 | 19 | 98 | 0 | 5 | 13 | 5 | 44 | 38 | 90 | 0.9 | 47 |
1,210 | llm | https://github.com/freedomintelligence/llmzoo | ['language-model'] | null | [] | [] | null | null | null | freedomintelligence/llmzoo | LLMZoo | 2,786 | 189 | 50 | Python | null | ⚡LLM Zoo is a project that provides data, models, and evaluation benchmark for large language models.⚡ | freedomintelligence | 2024-01-12 | 2023-04-01 | 43 | 64.151316 | https://avatars.githubusercontent.com/u/127706844?v=4 | ⚡LLM Zoo is a project that provides data, models, and evaluation benchmark for large language models.⚡ | [] | ['language-model'] | 2023-07-25 | [('ai21labs/lm-evaluation', 0.7427138090133667, 'llm', 1), ('hannibal046/awesome-llm', 0.7315229177474976, 'study', 1), ('lm-sys/fastchat', 0.6950333714485168, 'llm', 1), ('ctlllll/llm-toolmaker', 0.6779150366783142, 'llm', 1), ('eleutherai/lm-evaluation-harness', 0.6675116419792175, 'llm', 1), ('fasteval/fasteval', 0.... | 10 | 3 | null | 3.96 | 2 | 1 | 10 | 6 | 0 | 0 | 0 | 2 | 1 | 90 | 0.5 | 47 |
863 | profiling | https://github.com/reloadware/reloadium | [] | null | [] | [] | 1 | null | null | reloadware/reloadium | reloadium | 2,621 | 57 | 25 | Python | https://reloadium.io | Hot Reloading, Profiling and AI debugging for Python | reloadware | 2024-01-14 | 2022-01-15 | 106 | 24.626846 | https://avatars.githubusercontent.com/u/85869255?v=4 | Hot Reloading, Profiling and AI debugging for Python | ['ai', 'artificial-intelligence', 'chatgpt', 'django', 'edit-and-continue', 'flask', 'hot-reload', 'hot-reloading', 'pandas'] | ['ai', 'artificial-intelligence', 'chatgpt', 'django', 'edit-and-continue', 'flask', 'hot-reload', 'hot-reloading', 'pandas'] | 2024-01-04 | [('carla-recourse/carla', 0.5905767679214478, 'ml', 1), ('fastai/fastcore', 0.5807570219039917, 'util', 0), ('sourcery-ai/sourcery', 0.5745614767074585, 'util', 1), ('alexmojaki/snoop', 0.5736259818077087, 'debug', 0), ('eleutherai/pyfra', 0.5577932596206665, 'ml', 0), ('willmcgugan/textual', 0.5569230318069458, 'term'... | 3 | 2 | null | 0.27 | 14 | 11 | 24 | 0 | 0 | 3 | 3 | 14 | 19 | 90 | 1.4 | 47 |
307 | util | https://github.com/legrandin/pycryptodome | [] | null | [] | [] | null | null | null | legrandin/pycryptodome | pycryptodome | 2,582 | 468 | 63 | C | https://www.pycryptodome.org | A self-contained cryptographic library for Python | legrandin | 2024-01-14 | 2014-05-02 | 508 | 5.076966 | null | A self-contained cryptographic library for Python | ['cryptography', 'security'] | ['cryptography', 'security'] | 2024-01-13 | [('pyca/cryptography', 0.8198734521865845, 'util', 1), ('pyca/pynacl', 0.7229923605918884, 'util', 1), ('primal100/pybitcointools', 0.6471469402313232, 'crypto', 0), ('1200wd/bitcoinlib', 0.6432069540023804, 'crypto', 0), ('snyk/faker-security', 0.5843793153762817, 'security', 0), ('pytoolz/toolz', 0.5827405452728271, ... | 146 | 4 | null | 2.42 | 27 | 20 | 118 | 0 | 10 | 12 | 10 | 27 | 46 | 90 | 1.7 | 47 |
130 | viz | https://github.com/holoviz/holoviews | [] | null | [] | [] | null | null | null | holoviz/holoviews | holoviews | 2,550 | 386 | 58 | Python | https://holoviews.org | With Holoviews, your data visualizes itself. | holoviz | 2024-01-13 | 2014-05-07 | 507 | 5.021097 | https://avatars.githubusercontent.com/u/51678735?v=4 | With Holoviews, your data visualizes itself. | ['holoviews', 'holoviz', 'plotting'] | ['holoviews', 'holoviz', 'plotting'] | 2023-12-22 | [('holoviz/hvplot', 0.682068407535553, 'pandas', 3), ('holoviz/geoviews', 0.6530880331993103, 'gis', 3), ('holoviz/holoviz', 0.585200309753418, 'viz', 2), ('matplotlib/matplotlib', 0.564393937587738, 'viz', 1), ('facebookresearch/hiplot', 0.5553148984909058, 'viz', 0), ('holoviz/datashader', 0.5166183710098267, 'gis', ... | 140 | 4 | null | 5.21 | 176 | 82 | 118 | 1 | 8 | 41 | 8 | 174 | 226 | 90 | 1.3 | 47 |
1,731 | testing | https://github.com/kevin1024/vcrpy | [] | null | [] | [] | null | null | null | kevin1024/vcrpy | vcrpy | 2,547 | 363 | 38 | Python | null | Automatically mock your HTTP interactions to simplify and speed up testing | kevin1024 | 2024-01-12 | 2012-05-29 | 609 | 4.182266 | null | Automatically mock your HTTP interactions to simplify and speed up testing | ['http', 'mocking', 'testing'] | ['http', 'mocking', 'testing'] | 2024-01-05 | [('jamielennox/requests-mock', 0.6570014953613281, 'testing', 1), ('lundberg/respx', 0.6465907692909241, 'testing', 2), ('getsentry/responses', 0.5679908990859985, 'testing', 1)] | 139 | 5 | null | 2.52 | 66 | 40 | 142 | 0 | 5 | 5 | 5 | 66 | 125 | 90 | 1.9 | 47 |
867 | perf | https://github.com/ipython/ipyparallel | [] | null | [] | [] | null | null | null | ipython/ipyparallel | ipyparallel | 2,518 | 1,051 | 121 | Jupyter Notebook | https://ipyparallel.readthedocs.io/ | IPython Parallel: Interactive Parallel Computing in Python | ipython | 2024-01-13 | 2015-04-09 | 459 | 5.477315 | https://avatars.githubusercontent.com/u/230453?v=4 | IPython Parallel: Interactive Parallel Computing in Python | ['jupyter', 'parallel'] | ['jupyter', 'parallel'] | 2024-01-05 | [('jupyterlab/jupyterlab', 0.6818181872367859, 'jupyter', 1), ('ipython/ipykernel', 0.6646348237991333, 'util', 1), ('dask/dask', 0.64837247133255, 'perf', 0), ('pypy/pypy', 0.6435779333114624, 'util', 0), ('joblib/joblib', 0.6388868689537048, 'util', 0), ('maartenbreddels/ipyvolume', 0.6384920477867126, 'jupyter', 1),... | 113 | 6 | null | 1.63 | 21 | 12 | 107 | 0 | 0 | 7 | 7 | 21 | 36 | 90 | 1.7 | 47 |
439 | gis | https://github.com/rasterio/rasterio | [] | null | [] | [] | 1 | null | null | rasterio/rasterio | rasterio | 2,074 | 521 | 147 | Python | https://rasterio.readthedocs.io/ | Rasterio reads and writes geospatial raster datasets | rasterio | 2024-01-13 | 2013-11-04 | 534 | 3.882856 | https://avatars.githubusercontent.com/u/46967650?v=4 | Rasterio reads and writes geospatial raster datasets | ['cli', 'cython', 'gdal', 'gis', 'mapbox-satellite-oss', 'raster'] | ['cli', 'cython', 'gdal', 'gis', 'mapbox-satellite-oss', 'raster'] | 2024-01-09 | [('cogeotiff/rio-tiler', 0.7036706209182739, 'gis', 2), ('toblerity/fiona', 0.5375838279724121, 'gis', 4), ('corteva/rioxarray', 0.5225644707679749, 'gis', 3)] | 155 | 5 | null | 2.65 | 101 | 80 | 124 | 0 | 8 | 17 | 8 | 101 | 134 | 90 | 1.3 | 47 |
116 | perf | https://github.com/h5py/h5py | ['hdf5'] | null | [] | [] | null | null | null | h5py/h5py | h5py | 1,965 | 545 | 57 | Python | http://www.h5py.org | HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format. | h5py | 2024-01-12 | 2012-09-21 | 592 | 3.316056 | https://avatars.githubusercontent.com/u/2389852?v=4 | HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format. | [] | ['hdf5'] | 2024-01-12 | [] | 199 | 6 | null | 2.65 | 49 | 27 | 138 | 0 | 3 | 4 | 3 | 49 | 164 | 90 | 3.3 | 47 |
1,234 | llm | https://github.com/lucidrains/toolformer-pytorch | ['toolformer', 'language-model'] | null | [] | [] | null | null | null | lucidrains/toolformer-pytorch | toolformer-pytorch | 1,802 | 111 | 38 | Python | null | Implementation of Toolformer, Language Models That Can Use Tools, by MetaAI | lucidrains | 2024-01-14 | 2023-02-10 | 50 | 35.632768 | null | Implementation of Toolformer, Language Models That Can Use Tools, by MetaAI | ['api-calling', 'artificial-intelligence', 'attention-mechanisms', 'deep-learning', 'transformers'] | ['api-calling', 'artificial-intelligence', 'attention-mechanisms', 'deep-learning', 'language-model', 'toolformer', 'transformers'] | 2023-12-21 | [('conceptofmind/toolformer', 0.7667592167854309, 'llm', 2), ('ctlllll/llm-toolmaker', 0.6329768300056458, 'llm', 1), ('lm-sys/fastchat', 0.6176435947418213, 'llm', 1), ('huggingface/transformers', 0.6121810674667358, 'nlp', 2), ('thilinarajapakse/simpletransformers', 0.6100559234619141, 'nlp', 1), ('oobabooga/text-gen... | 3 | 1 | null | 1.17 | 9 | 2 | 11 | 1 | 24 | 27 | 24 | 9 | 10 | 90 | 1.1 | 47 |
1,093 | ml-interpretability | https://github.com/eleutherai/pythia | ['interpretability', 'interpretable-ml'] | Interpretability analysis and scaling laws to understand how knowledge develops and evolves during training in autoregressive transformers | [] | [] | null | null | null | eleutherai/pythia | pythia | 1,801 | 117 | 29 | Jupyter Notebook | null | The hub for EleutherAI's work on interpretability and learning dynamics | eleutherai | 2024-01-13 | 2021-12-25 | 109 | 16.458225 | https://avatars.githubusercontent.com/u/68924597?v=4 | The hub for EleutherAI's work on interpretability and learning dynamics | [] | ['interpretability', 'interpretable-ml'] | 2023-12-31 | [('pair-code/lit', 0.641786515712738, 'ml-interpretability', 0), ('csinva/imodels', 0.5875741243362427, 'ml', 1), ('tensorflow/lucid', 0.5809341669082642, 'ml-interpretability', 1), ('marcotcr/lime', 0.5768492817878723, 'ml-interpretability', 1), ('interpretml/interpret', 0.5574303269386292, 'ml-interpretability', 2), ... | 17 | 4 | null | 3.37 | 30 | 23 | 25 | 0 | 0 | 0 | 0 | 30 | 36 | 90 | 1.2 | 47 |
1,116 | web | https://github.com/cherrypy/cherrypy | [] | null | [] | [] | null | null | null | cherrypy/cherrypy | cherrypy | 1,748 | 359 | 55 | Python | https://docs.cherrypy.dev | CherryPy is a pythonic, object-oriented HTTP framework. https://cherrypy.dev | cherrypy | 2024-01-10 | 2016-04-30 | 404 | 4.322148 | https://avatars.githubusercontent.com/u/6617466?v=4 | CherryPy is a pythonic, object-oriented HTTP framework. https://cherrypy.dev | ['cherrypy', 'cross-platform', 'daemon-mode', 'http', 'http-server', 'http-streaming', 'https', 'idiomatic-python', 'jython', 'pure-python', 'pypy', 'pypy3'] | ['cherrypy', 'cross-platform', 'daemon-mode', 'http', 'http-server', 'http-streaming', 'https', 'idiomatic-python', 'jython', 'pure-python', 'pypy', 'pypy3'] | 2024-01-05 | [('bottlepy/bottle', 0.6888998746871948, 'web', 0), ('webpy/webpy', 0.6774104833602905, 'web', 0), ('encode/httpx', 0.65858393907547, 'web', 1), ('encode/uvicorn', 0.6493438482284546, 'web', 2), ('masoniteframework/masonite', 0.6259151697158813, 'web', 0), ('pallets/flask', 0.6162318587303162, 'web', 0), ('neoteroi/bla... | 143 | 7 | null | 0.5 | 22 | 15 | 94 | 0 | 0 | 17 | 17 | 22 | 54 | 90 | 2.5 | 47 |
1,824 | llm | https://github.com/noahshinn/reflexion | [] | null | [] | [] | null | null | null | noahshinn/reflexion | reflexion | 1,697 | 160 | 29 | Python | null | [NeurIPS 2023] Reflexion: Language Agents with Verbal Reinforcement Learning | noahshinn | 2024-01-14 | 2023-03-22 | 44 | 37.83121 | null | [NeurIPS 2023] Reflexion: Language Agents with Verbal Reinforcement Learning | ['ai', 'artificial-intelligence', 'llm'] | ['ai', 'artificial-intelligence', 'llm'] | 2023-11-26 | [('aiwaves-cn/agents', 0.5806130170822144, 'nlp', 1), ('jina-ai/thinkgpt', 0.5254539847373962, 'llm', 0), ('lupantech/scienceqa', 0.5062936544418335, 'llm', 0), ('oliveirabruno01/babyagi-asi', 0.5022252798080444, 'llm', 1), ('humanoidagents/humanoidagents', 0.5013625621795654, 'sim', 0), ('thilinarajapakse/simpletransf... | 7 | 3 | null | 3.15 | 13 | 9 | 10 | 2 | 0 | 0 | 0 | 13 | 16 | 90 | 1.2 | 47 |
427 | jupyter | https://github.com/jupyter-lsp/jupyterlab-lsp | [] | null | [] | [] | null | null | null | jupyter-lsp/jupyterlab-lsp | jupyterlab-lsp | 1,663 | 134 | 20 | TypeScript | null | Coding assistance for JupyterLab (code navigation + hover suggestions + linters + autocompletion + rename) using Language Server Protocol | jupyter-lsp | 2024-01-13 | 2019-08-17 | 232 | 7.154886 | https://avatars.githubusercontent.com/u/92232904?v=4 | Coding assistance for JupyterLab (code navigation + hover suggestions + linters + autocompletion + rename) using Language Server Protocol | ['autocompletion', 'ipython', 'julia-language', 'jupyter', 'jupyter-lab', 'jupyter-notebook', 'jupyterlab', 'jupyterlab-extension', 'language-server-protocol', 'linter', 'lsp', 'notebook', 'notebook-jupyter', 'r'] | ['autocompletion', 'ipython', 'julia-language', 'jupyter', 'jupyter-lab', 'jupyter-notebook', 'jupyterlab', 'jupyterlab-extension', 'language-server-protocol', 'linter', 'lsp', 'notebook', 'notebook-jupyter', 'r'] | 2023-11-26 | [('mwouts/jupytext', 0.6457168459892273, 'jupyter', 3), ('jupyter-widgets/ipywidgets', 0.5988917946815491, 'jupyter', 1), ('cohere-ai/notebooks', 0.5917092561721802, 'llm', 0), ('jupyter/notebook', 0.5912204384803772, 'jupyter', 3), ('jupyterlab/jupyterlab', 0.5912031531333923, 'jupyter', 2), ('jupyterlab/jupyterlab-de... | 51 | 5 | null | 5.02 | 49 | 34 | 54 | 2 | 12 | 12 | 12 | 49 | 75 | 90 | 1.5 | 47 |
1,075 | util | https://github.com/rhettbull/osxphotos | [] | null | [] | [] | null | null | null | rhettbull/osxphotos | osxphotos | 1,521 | 85 | 21 | Python | null | Python app to export pictures and associated metadata from Apple Photos on macOS. Also includes a package to provide programmatic access to the Photos library, pictures, and metadata. | rhettbull | 2024-01-13 | 2019-06-16 | 241 | 6.30373 | null | Python app to export pictures and associated metadata from Apple Photos on macOS. Also includes a package to provide programmatic access to the Photos library, pictures, and metadata. | ['apple', 'apple-photos', 'apple-photos-export', 'library-photos', 'macos', 'macosx', 'osx', 'photos', 'photos-database', 'photos-export', 'pictures'] | ['apple', 'apple-photos', 'apple-photos-export', 'library-photos', 'macos', 'macosx', 'osx', 'photos', 'photos-database', 'photos-export', 'pictures'] | 2024-01-13 | [('imageio/imageio', 0.6166835427284241, 'util', 0), ('python-pillow/pillow', 0.5487352609634399, 'util', 0), ('python-odin/odin', 0.5156180262565613, 'util', 0), ('erotemic/ubelt', 0.5059564709663391, 'util', 0)] | 35 | 2 | null | 6.46 | 129 | 99 | 56 | 0 | 50 | 98 | 50 | 129 | 231 | 90 | 1.8 | 47 |
1,559 | nlp | https://github.com/marella/ctransformers | [] | null | [] | [] | null | null | null | marella/ctransformers | ctransformers | 1,510 | 118 | 18 | C | null | Python bindings for the Transformer models implemented in C/C++ using GGML library. | marella | 2024-01-14 | 2023-05-14 | 37 | 40.498084 | null | Python bindings for the Transformer models implemented in C/C++ using GGML library. | ['ai', 'ctransformers', 'llm', 'transformers'] | ['ai', 'ctransformers', 'llm', 'transformers'] | 2023-09-10 | [('alignmentresearch/tuned-lens', 0.5659533143043518, 'ml-interpretability', 1), ('huggingface/transformers', 0.5550124645233154, 'nlp', 0), ('nielsrogge/transformers-tutorials', 0.553908109664917, 'study', 1), ('google/jax', 0.5531230568885803, 'ml', 0), ('eleutherai/gpt-neox', 0.5529630184173584, 'llm', 1), ('pybind/... | 6 | 0 | null | 2.77 | 56 | 10 | 8 | 4 | 30 | 46 | 30 | 56 | 72 | 90 | 1.3 | 47 |
402 | perf | https://github.com/agronholm/anyio | [] | null | [] | [] | null | null | null | agronholm/anyio | anyio | 1,482 | 117 | 27 | Python | null | High level asynchronous concurrency and networking framework that works on top of either trio or asyncio | agronholm | 2024-01-13 | 2018-08-19 | 284 | 5.213065 | null | High level asynchronous concurrency and networking framework that works on top of either trio or asyncio | ['async-await', 'asyncio', 'curio', 'trio'] | ['async-await', 'asyncio', 'curio', 'trio'] | 2024-01-13 | [('python-trio/trio', 0.8090512156486511, 'perf', 2), ('magicstack/uvloop', 0.7205407619476318, 'util', 2), ('tiangolo/asyncer', 0.7173997759819031, 'perf', 2), ('aio-libs/aiohttp', 0.6634643077850342, 'web', 1), ('samuelcolvin/arq', 0.6350996494293213, 'data', 1), ('noxdafox/pebble', 0.6101366281509399, 'perf', 1), ('... | 46 | 4 | null | 2.98 | 56 | 48 | 66 | 0 | 3 | 9 | 3 | 56 | 200 | 90 | 3.6 | 47 |
621 | data | https://github.com/zarr-developers/zarr-python | [] | null | [] | [] | null | null | null | zarr-developers/zarr-python | zarr-python | 1,274 | 263 | 46 | Python | http://zarr.readthedocs.io/ | An implementation of chunked, compressed, N-dimensional arrays for Python. | zarr-developers | 2024-01-13 | 2015-12-15 | 424 | 3.004717 | https://avatars.githubusercontent.com/u/35050297?v=4 | An implementation of chunked, compressed, N-dimensional arrays for Python. | ['compressed', 'ndimensional-arrays', 'zarr'] | ['compressed', 'ndimensional-arrays', 'zarr'] | 2024-01-10 | [('google/tensorstore', 0.668194591999054, 'data', 0), ('blosc/python-blosc', 0.5569503903388977, 'perf', 0), ('pyston/pyston', 0.5102282762527466, 'util', 0), ('pydata/xarray', 0.5044090151786804, 'util', 0)] | 95 | 8 | null | 2.67 | 148 | 88 | 98 | 0 | 11 | 11 | 11 | 148 | 242 | 90 | 1.6 | 47 |
764 | data | https://github.com/google/tensorstore | [] | null | [] | [] | null | null | null | google/tensorstore | tensorstore | 1,248 | 103 | 31 | C++ | https://google.github.io/tensorstore/ | Library for reading and writing large multi-dimensional arrays. | google | 2024-01-12 | 2020-03-30 | 200 | 6.235546 | https://avatars.githubusercontent.com/u/1342004?v=4 | Library for reading and writing large multi-dimensional arrays. | [] | [] | 2024-01-04 | [('zarr-developers/zarr-python', 0.668194591999054, 'data', 0), ('xl0/lovely-numpy', 0.5052934288978577, 'util', 0)] | 22 | 3 | null | 8.33 | 18 | 10 | 46 | 0 | 0 | 14 | 14 | 18 | 54 | 90 | 3 | 47 |
572 | util | https://github.com/fsspec/filesystem_spec | [] | null | [] | [] | null | null | null | fsspec/filesystem_spec | filesystem_spec | 723 | 308 | 20 | Python | null | A specification that python filesystems should adhere to. | fsspec | 2024-01-14 | 2018-04-23 | 301 | 2.400854 | https://avatars.githubusercontent.com/u/92825505?v=4 | A specification that python filesystems should adhere to. | [] | [] | 2024-01-13 | [('pyfilesystem/pyfilesystem2', 0.7090234160423279, 'util', 0), ('tox-dev/py-filelock', 0.6173799633979797, 'util', 0), ('platformdirs/platformdirs', 0.5413647294044495, 'util', 0), ('grantjenks/python-diskcache', 0.5200872421264648, 'util', 0), ('pytoolz/toolz', 0.5183253288269043, 'util', 0), ('google/yapf', 0.512998... | 223 | 9 | null | 3.63 | 124 | 87 | 70 | 0 | 0 | 13 | 13 | 124 | 296 | 90 | 2.4 | 47 |
1,324 | util | https://github.com/anthropics/anthropic-sdk-python | ['sdk', 'language-model', 'api'] | SDK providing access to Anthropic's safety-first language model APIs | [] | [] | null | null | null | anthropics/anthropic-sdk-python | anthropic-sdk-python | 584 | 65 | 42 | Python | null | null | anthropics | 2024-01-13 | 2023-01-17 | 54 | 10.814815 | https://avatars.githubusercontent.com/u/76263028?v=4 | SDK providing access to Anthropic's safety-first language model APIs | [] | ['api', 'language-model', 'sdk'] | 2024-01-08 | [('langchain-ai/langsmith-sdk', 0.5629613995552063, 'llm', 1), ('cohere-ai/cohere-python', 0.5114951133728027, 'util', 1), ('kubeflow/fairing', 0.5095229148864746, 'ml-ops', 0)] | 16 | 5 | null | 4.38 | 120 | 119 | 12 | 0 | 42 | 43 | 42 | 120 | 57 | 90 | 0.5 | 47 |
1,733 | ml | https://github.com/qdrant/fastembed | ['vectordb'] | null | [] | [] | null | null | null | qdrant/fastembed | fastembed | 503 | 27 | 7 | Jupyter Notebook | https://qdrant.github.io/fastembed/ | Fast, Accurate, Lightweight Python library to make State of the Art Embedding | qdrant | 2024-01-12 | 2023-07-14 | 28 | 17.605 | https://avatars.githubusercontent.com/u/73504361?v=4 | Fast, Accurate, Lightweight Python library to make State of the Art Embedding | ['embeddings', 'openai', 'rag', 'retrieval', 'retrieval-augmented-generation', 'vector-search'] | ['embeddings', 'openai', 'rag', 'retrieval', 'retrieval-augmented-generation', 'vector-search', 'vectordb'] | 2023-12-13 | [('chroma-core/chroma', 0.7453431487083435, 'data', 2), ('jina-ai/vectordb', 0.7195001244544983, 'data', 2), ('neuml/txtai', 0.6601556539535522, 'nlp', 4), ('kagisearch/vectordb', 0.6594275832176208, 'data', 1), ('plasticityai/magnitude', 0.6370154619216919, 'nlp', 1), ('koaning/embetter', 0.6213396787643433, 'data', 0... | 7 | 3 | null | 5.75 | 70 | 46 | 6 | 1 | 3 | 20 | 3 | 70 | 125 | 90 | 1.8 | 47 |
1,606 | llm | https://github.com/opengvlab/omniquant | [] | null | [] | [] | null | null | null | opengvlab/omniquant | OmniQuant | 457 | 36 | 13 | Python | null | OmniQuant is a simple and powerful quantization technique for LLMs. | opengvlab | 2024-01-12 | 2023-08-22 | 23 | 19.869565 | https://avatars.githubusercontent.com/u/94522163?v=4 | OmniQuant is a simple and powerful quantization technique for LLMs. | ['large-language-models', 'llm', 'quantization'] | ['large-language-models', 'llm', 'quantization'] | 2023-12-27 | [('artidoro/qlora', 0.7345274090766907, 'llm', 0), ('squeezeailab/squeezellm', 0.6535307168960571, 'llm', 3), ('vahe1994/spqr', 0.6055932641029358, 'llm', 1), ('bobazooba/xllm', 0.5902096033096313, 'llm', 2), ('lightning-ai/lit-gpt', 0.5481755137443542, 'llm', 1), ('lightning-ai/lit-llama', 0.5302090048789978, 'llm', 0... | 12 | 6 | null | 0.63 | 38 | 29 | 5 | 1 | 1 | 2 | 1 | 38 | 99 | 90 | 2.6 | 47 |
782 | study | https://github.com/wesm/pydata-book | [] | null | [] | [] | null | null | null | wesm/pydata-book | pydata-book | 20,766 | 14,692 | 1,476 | Jupyter Notebook | null | Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media | wesm | 2024-01-14 | 2012-06-30 | 604 | 34.356417 | null | Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media | [] | [] | 2023-04-12 | [('jakevdp/pythondatasciencehandbook', 0.7202770709991455, 'study', 0), ('fchollet/deep-learning-with-python-notebooks', 0.6737366318702698, 'study', 0), ('python/cpython', 0.6508677005767822, 'util', 0), ('pandas-dev/pandas', 0.6384697556495667, 'pandas', 0), ('mynameisfiber/high_performance_python_2e', 0.634195029735... | 9 | 5 | null | 0.06 | 6 | 3 | 140 | 9 | 0 | 0 | 0 | 6 | 4 | 90 | 0.7 | 46 |
187 | ml | https://github.com/harisiqbal88/plotneuralnet | ['diagrams', 'latex'] | null | [] | [] | null | null | null | harisiqbal88/plotneuralnet | PlotNeuralNet | 20,540 | 2,735 | 229 | TeX | null | Latex code for making neural networks diagrams | harisiqbal88 | 2024-01-13 | 2018-07-24 | 288 | 71.319444 | null | Latex code for making neural networks diagrams | ['deep-neural-networks', 'latex'] | ['deep-neural-networks', 'diagrams', 'latex'] | 2020-11-06 | [('lutzroeder/netron', 0.542097270488739, 'ml', 0)] | 13 | 6 | null | 0 | 0 | 0 | 67 | 39 | 0 | 0 | 0 | 0 | 0 | 90 | 0 | 46 |
145 | llm | https://github.com/openai/gpt-2 | [] | null | [] | [] | null | null | null | openai/gpt-2 | gpt-2 | 20,469 | 5,247 | 635 | Python | https://openai.com/blog/better-language-models/ | Code for the paper "Language Models are Unsupervised Multitask Learners" | openai | 2024-01-13 | 2019-02-11 | 259 | 78.987321 | https://avatars.githubusercontent.com/u/14957082?v=4 | Code for the paper "Language Models are Unsupervised Multitask Learners" | ['paper'] | ['paper'] | 2020-12-02 | [('openai/finetune-transformer-lm', 0.6553829312324524, 'llm', 1), ('yueyu1030/attrprompt', 0.5717838406562805, 'llm', 0), ('jonasgeiping/cramming', 0.5695840716362, 'nlp', 0), ('hannibal046/awesome-llm', 0.5629648566246033, 'study', 0), ('tatsu-lab/stanford_alpaca', 0.5557239055633545, 'llm', 0), ('facebookresearch/co... | 16 | 2 | null | 0 | 3 | 1 | 60 | 38 | 0 | 0 | 0 | 3 | 1 | 90 | 0.3 | 46 |
149 | data | https://github.com/twintproject/twint | [] | null | [] | [] | null | null | null | twintproject/twint | twint | 15,365 | 2,744 | 322 | Python | null | An advanced Twitter scraping & OSINT tool written in Python that doesn't use Twitter's API, allowing you to scrape a user's followers, following, Tweets and more while evading most API limitations. | twintproject | 2024-01-13 | 2017-06-10 | 346 | 44.352577 | https://avatars.githubusercontent.com/u/40190352?v=4 | An advanced Twitter scraping & OSINT tool written in Python that doesn't use Twitter's API, allowing you to scrape a user's followers, following, Tweets and more while evading most API limitations. | ['elasticsearch', 'kibana', 'osint', 'scrape', 'scrape-followers', 'scrape-following', 'scrape-likes', 'tweep', 'tweets', 'twint', 'twitter'] | ['elasticsearch', 'kibana', 'osint', 'scrape', 'scrape-followers', 'scrape-following', 'scrape-likes', 'tweep', 'tweets', 'twint', 'twitter'] | 2021-03-02 | [('sherlock-project/sherlock', 0.5957009196281433, 'web', 1), ('alirezamika/autoscraper', 0.5726699233055115, 'data', 1), ('scrapy/scrapy', 0.5525391101837158, 'data', 0), ('roniemartinez/dude', 0.5376254916191101, 'util', 0)] | 65 | 4 | null | 0 | 1 | 1 | 80 | 35 | 0 | 4 | 4 | 1 | 0 | 90 | 0 | 46 |
1,058 | ml | https://github.com/ddbourgin/numpy-ml | [] | null | [] | [] | null | null | null | ddbourgin/numpy-ml | numpy-ml | 14,370 | 3,641 | 452 | Python | https://numpy-ml.readthedocs.io/ | Machine learning, in numpy | ddbourgin | 2024-01-14 | 2019-04-06 | 251 | 57.153409 | null | Machine learning, in numpy | ['attention', 'bayesian-inference', 'gaussian-mixture-models', 'gaussian-processes', 'good-turing-smoothing', 'gradient-boosting', 'hidden-markov-models', 'knn', 'lstm', 'machine-learning', 'mfcc', 'neural-networks', 'reinforcement-learning', 'resnet', 'topic-modeling', 'vae', 'wavenet', 'wgan-gp', 'word2vec'] | ['attention', 'bayesian-inference', 'gaussian-mixture-models', 'gaussian-processes', 'good-turing-smoothing', 'gradient-boosting', 'hidden-markov-models', 'knn', 'lstm', 'machine-learning', 'mfcc', 'neural-networks', 'reinforcement-learning', 'resnet', 'topic-modeling', 'vae', 'wavenet', 'wgan-gp', 'word2vec'] | 2022-01-08 | [('mosaicml/composer', 0.6701366305351257, 'ml-dl', 2), ('huggingface/datasets', 0.6540278196334839, 'nlp', 1), ('google/trax', 0.6432744264602661, 'ml-dl', 2), ('huggingface/transformers', 0.6313506960868835, 'nlp', 1), ('onnx/onnx', 0.6284279227256775, 'ml', 1), ('tensorflow/tensorflow', 0.6283783912658691, 'ml-dl', ... | 16 | 5 | null | 0 | 4 | 0 | 58 | 24 | 0 | 0 | 0 | 4 | 1 | 90 | 0.2 | 46 |
218 | ml | https://github.com/spotify/annoy | [] | null | [] | [] | 1 | null | null | spotify/annoy | annoy | 12,337 | 1,171 | 322 | C++ | null | Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk | spotify | 2024-01-13 | 2013-04-01 | 565 | 21.829879 | https://avatars.githubusercontent.com/u/251374?v=4 | Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk | ['approximate-nearest-neighbor-search', 'c-plus-plus', 'golang', 'locality-sensitive-hashing', 'lua', 'nearest-neighbor-search'] | ['approximate-nearest-neighbor-search', 'c-plus-plus', 'golang', 'locality-sensitive-hashing', 'lua', 'nearest-neighbor-search'] | 2023-08-20 | [('nmslib/hnswlib', 0.7858440279960632, 'ml', 0), ('spotify/voyager', 0.6272151470184326, 'ml', 1), ('lmcinnes/pynndescent', 0.6271777749061584, 'ml', 2), ('dgilland/cacheout', 0.5922878980636597, 'perf', 0), ('erotemic/ubelt', 0.5622727870941162, 'util', 0), ('cython/cython', 0.5542510151863098, 'util', 0), ('pyston/p... | 88 | 2 | null | 0.6 | 3 | 0 | 131 | 5 | 2 | 3 | 2 | 3 | 3 | 90 | 1 | 46 |
1,006 | finance | https://github.com/mementum/backtrader | [] | null | [] | [] | 1 | null | null | mementum/backtrader | backtrader | 12,322 | 3,618 | 601 | Python | https://www.backtrader.com | Python Backtesting library for trading strategies | mementum | 2024-01-14 | 2015-01-10 | 472 | 26.08225 | null | Python Backtesting library for trading strategies | ['backtesting', 'metaclass', 'trading'] | ['backtesting', 'metaclass', 'trading'] | 2023-04-19 | [('cuemacro/finmarketpy', 0.8932955265045166, 'finance', 0), ('gbeced/pyalgotrade', 0.6685662269592285, 'finance', 0), ('kernc/backtesting.py', 0.6531647443771362, 'finance', 2), ('pmorissette/bt', 0.6390605568885803, 'finance', 0), ('robcarver17/pysystemtrade', 0.6113889813423157, 'finance', 0), ('goldmansachs/gs-quan... | 56 | 2 | null | 0.31 | 6 | 3 | 110 | 9 | 0 | 15 | 15 | 6 | 1 | 90 | 0.2 | 46 |
111 | ml-interpretability | https://github.com/marcotcr/lime | ['interpretable-ml'] | null | [] | [] | null | null | null | marcotcr/lime | lime | 11,075 | 1,798 | 264 | JavaScript | null | Lime: Explaining the predictions of any machine learning classifier | marcotcr | 2024-01-13 | 2016-03-15 | 411 | 26.946472 | null | Lime: Explaining the predictions of any machine learning classifier | [] | ['interpretable-ml'] | 2021-07-29 | [('seldonio/alibi', 0.7131057977676392, 'ml-interpretability', 0), ('pair-code/lit', 0.6946200132369995, 'ml-interpretability', 0), ('maif/shapash', 0.6499969363212585, 'ml', 0), ('csinva/imodels', 0.6466513276100159, 'ml', 0), ('teamhg-memex/eli5', 0.6452601552009583, 'ml', 0), ('slundberg/shap', 0.6387524604797363, '... | 62 | 5 | null | 0 | 9 | 2 | 95 | 30 | 0 | 2 | 2 | 9 | 8 | 90 | 0.9 | 46 |
746 | study | https://github.com/karpathy/nn-zero-to-hero | [] | null | [] | [] | null | null | null | karpathy/nn-zero-to-hero | nn-zero-to-hero | 9,163 | 1,068 | 259 | Jupyter Notebook | null | Neural Networks: Zero to Hero | karpathy | 2024-01-13 | 2022-09-08 | 72 | 126.013752 | null | Neural Networks: Zero to Hero | [] | [] | 2023-01-17 | [('rasbt/deeplearning-models', 0.5198577642440796, 'ml-dl', 0), ('mosaicml/composer', 0.5013008713722229, 'ml-dl', 0)] | 2 | 0 | null | 0 | 4 | 3 | 16 | 12 | 0 | 0 | 0 | 4 | 3 | 90 | 0.8 | 46 |
230 | template | https://github.com/drivendata/cookiecutter-data-science | [] | null | [] | [] | 1 | null | null | drivendata/cookiecutter-data-science | cookiecutter-data-science | 7,324 | 2,282 | 120 | Python | http://drivendata.github.io/cookiecutter-data-science/ | A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. | drivendata | 2024-01-13 | 2015-10-30 | 430 | 17.009954 | null | A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. | ['ai', 'cookiecutter', 'cookiecutter-data-science', 'cookiecutter-template', 'data-science', 'machine-learning'] | ['ai', 'cookiecutter', 'cookiecutter-data-science', 'cookiecutter-template', 'data-science', 'machine-learning'] | 2023-09-22 | [('crmne/cookiecutter-modern-datascience', 0.7191076874732971, 'template', 3), ('airbnb/knowledge-repo', 0.5590470433235168, 'data', 1), ('netflix/metaflow', 0.5439575910568237, 'ml-ops', 3), ('onnx/onnx', 0.5203287601470947, 'ml', 1), ('avaiga/taipy', 0.519536018371582, 'data', 0), ('meltano/meltano', 0.50922513008117... | 46 | 6 | null | 0.02 | 23 | 11 | 100 | 4 | 0 | 0 | 0 | 24 | 22 | 90 | 0.9 | 46 |
453 | ml-rl | https://github.com/tensorlayer/tensorlayer | [] | null | [] | [] | null | null | null | tensorlayer/tensorlayer | TensorLayer | 7,264 | 1,636 | 461 | Python | http://tensorlayerx.com | Deep Learning and Reinforcement Learning Library for Scientists and Engineers | tensorlayer | 2024-01-12 | 2016-06-07 | 399 | 18.205514 | https://avatars.githubusercontent.com/u/32261543?v=4 | Deep Learning and Reinforcement Learning Library for Scientists and Engineers | ['a3c', 'artificial-intelligence', 'chatbot', 'deep-learning', 'dqn', 'gan', 'google', 'imagenet', 'neural-network', 'object-detection', 'reinforcement-learning', 'tensorflow', 'tensorflow-tutorial', 'tensorflow-tutorials', 'tensorlayer'] | ['a3c', 'artificial-intelligence', 'chatbot', 'deep-learning', 'dqn', 'gan', 'google', 'imagenet', 'neural-network', 'object-detection', 'reinforcement-learning', 'tensorflow', 'tensorflow-tutorial', 'tensorflow-tutorials', 'tensorlayer'] | 2023-02-18 | [('pytorch/rl', 0.7300659418106079, 'ml-rl', 1), ('keras-rl/keras-rl', 0.6922048926353455, 'ml-rl', 2), ('tensorflow/tensor2tensor', 0.6871770024299622, 'ml', 2), ('explosion/thinc', 0.6832032203674316, 'ml-dl', 3), ('google/trax', 0.6657304167747498, 'ml-dl', 2), ('keras-team/keras', 0.6656548976898193, 'ml-dl', 2), (... | 134 | 6 | null | 0.02 | 2 | 0 | 93 | 11 | 0 | 11 | 11 | 2 | 1 | 90 | 0.5 | 46 |
1,462 | util | https://github.com/hugapi/hug | [] | null | [] | [] | null | null | null | hugapi/hug | hug | 6,756 | 389 | 161 | Python | null | Embrace the APIs of the future. Hug aims to make developing APIs as simple as possible, but no simpler. | hugapi | 2024-01-13 | 2015-07-17 | 445 | 15.162552 | https://avatars.githubusercontent.com/u/49378345?v=4 | Embrace the APIs of the future. Hug aims to make developing APIs as simple as possible, but no simpler. | ['command-line', 'falcon', 'http', 'http-server', 'hug-api', 'python-api'] | ['command-line', 'falcon', 'http', 'http-server', 'hug-api', 'python-api'] | 2023-06-30 | [('vitalik/django-ninja', 0.6697272658348083, 'web', 0), ('tiangolo/fastapi', 0.6468743085861206, 'web', 0), ('falconry/falcon', 0.6300604343414307, 'web', 1), ('simple-salesforce/simple-salesforce', 0.6207526922225952, 'data', 0), ('python-restx/flask-restx', 0.6121255159378052, 'web', 0), ('asacristani/fastapi-rocket... | 120 | 6 | null | 0.08 | 1 | 0 | 103 | 7 | 0 | 7 | 7 | 1 | 1 | 90 | 1 | 46 |
1,117 | web | https://github.com/webpy/webpy | [] | null | [] | [] | null | null | null | webpy/webpy | webpy | 5,856 | 1,325 | 337 | Python | http://webpy.org | web.py is a web framework for python that is as simple as it is powerful. | webpy | 2024-01-13 | 2008-09-29 | 800 | 7.318693 | https://avatars.githubusercontent.com/u/26682?v=4 | web.py is a web framework for python that is as simple as it is powerful. | [] | [] | 2024-01-12 | [('bottlepy/bottle', 0.7816590070724487, 'web', 0), ('pallets/flask', 0.7347891926765442, 'web', 0), ('masoniteframework/masonite', 0.7172554731369019, 'web', 0), ('reflex-dev/reflex', 0.702220618724823, 'web', 0), ('cherrypy/cherrypy', 0.6774104833602905, 'web', 0), ('clips/pattern', 0.6514905095100403, 'nlp', 0), ('p... | 90 | 5 | null | 0.17 | 14 | 7 | 186 | 0 | 1 | 1 | 1 | 14 | 31 | 90 | 2.2 | 46 |
757 | ml-dl | https://github.com/xpixelgroup/basicsr | [] | null | [] | [] | null | null | null | xpixelgroup/basicsr | BasicSR | 5,775 | 1,036 | 96 | Python | https://basicsr.readthedocs.io/en/latest/ | Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet. | xpixelgroup | 2024-01-13 | 2018-04-19 | 301 | 19.140625 | https://avatars.githubusercontent.com/u/104772975?v=4 | Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet. | ['basicsr', 'basicvsr', 'dfdnet', 'ecbsr', 'edsr', 'edvr', 'esrgan', 'pytorch', 'rcan', 'restoration', 'srgan', 'srresnet', 'stylegan2', 'super-resolution', 'swinir'] | ['basicsr', 'basicvsr', 'dfdnet', 'ecbsr', 'edsr', 'edvr', 'esrgan', 'pytorch', 'rcan', 'restoration', 'srgan', 'srresnet', 'stylegan2', 'super-resolution', 'swinir'] | 2023-02-02 | [('xinntao/real-esrgan', 0.6734346151351929, 'ml-dl', 3), ('tencentarc/gfpgan', 0.6321846842765808, 'ml', 2), ('open-mmlab/mmediting', 0.5552972555160522, 'ml', 2)] | 19 | 7 | null | 0.06 | 32 | 2 | 70 | 12 | 0 | 6 | 6 | 32 | 25 | 90 | 0.8 | 46 |
1,646 | util | https://github.com/prompt-toolkit/ptpython | ['repl', 'cli'] | null | [] | [] | 1 | null | null | prompt-toolkit/ptpython | ptpython | 4,969 | 316 | 66 | Python | null | A better Python REPL | prompt-toolkit | 2024-01-13 | 2014-09-29 | 487 | 10.200293 | https://avatars.githubusercontent.com/u/44159252?v=4 | A better Python REPL | [] | ['cli', 'repl'] | 2023-12-14 | [('dosisod/refurb', 0.573533296585083, 'util', 1), ('google/python-fire', 0.5544407367706299, 'term', 1), ('urwid/urwid', 0.5443150997161865, 'term', 0), ('python/cpython', 0.5359960794448853, 'util', 0), ('sourcery-ai/sourcery', 0.5356951355934143, 'util', 0), ('pypy/pypy', 0.532114565372467, 'util', 0), ('pypi/wareho... | 58 | 4 | null | 0.52 | 24 | 13 | 113 | 1 | 2 | 4 | 2 | 24 | 30 | 90 | 1.2 | 46 |
636 | util | https://github.com/pycqa/pycodestyle | [] | null | [] | [] | null | null | null | pycqa/pycodestyle | pycodestyle | 4,941 | 809 | 117 | Python | https://pycodestyle.pycqa.org | Simple Python style checker in one Python file | pycqa | 2024-01-13 | 2009-10-02 | 747 | 6.609402 | https://avatars.githubusercontent.com/u/8749848?v=4 | Simple Python style checker in one Python file | ['flake8-plugin', 'linter-flake8', 'linter-plugin', 'pep8', 'style-guide', 'styleguide'] | ['flake8-plugin', 'linter-flake8', 'linter-plugin', 'pep8', 'style-guide', 'styleguide'] | 2024-01-08 | [('pycqa/flake8', 0.6883364915847778, 'util', 4), ('pycqa/mccabe', 0.5681533813476562, 'util', 3), ('hhatto/autopep8', 0.5678965449333191, 'util', 1), ('pycqa/pyflakes', 0.5580477118492126, 'util', 0), ('landscapeio/prospector', 0.531697690486908, 'util', 0), ('microsoft/pyright', 0.5176783204078674, 'typing', 0), ('ag... | 133 | 4 | null | 0.88 | 24 | 21 | 174 | 0 | 0 | 3 | 3 | 24 | 35 | 90 | 1.5 | 46 |
1,268 | perf | https://github.com/ultrajson/ultrajson | [] | null | [] | [] | null | null | null | ultrajson/ultrajson | ultrajson | 4,180 | 374 | 87 | C | https://pypi.org/project/ujson/ | Ultra fast JSON decoder and encoder written in C with Python bindings | ultrajson | 2024-01-12 | 2011-02-27 | 674 | 6.199153 | https://avatars.githubusercontent.com/u/61062879?v=4 | Ultra fast JSON decoder and encoder written in C with Python bindings | ['c', 'decoder', 'encoder', 'json', 'ujson', 'ultrajson'] | ['c', 'decoder', 'encoder', 'json', 'ujson', 'ultrajson'] | 2024-01-05 | [('cython/cython', 0.5291088223457336, 'util', 1), ('pypy/pypy', 0.5242108106613159, 'util', 0), ('blosc/python-blosc', 0.5216162204742432, 'perf', 0)] | 87 | 4 | null | 0.9 | 11 | 10 | 157 | 0 | 2 | 2 | 2 | 11 | 34 | 90 | 3.1 | 46 |
59 | gamedev | https://github.com/panda3d/panda3d | [] | null | [] | [] | null | null | null | panda3d/panda3d | panda3d | 4,140 | 780 | 199 | C++ | https://www.panda3d.org/ | Powerful, mature open-source cross-platform game engine for Python and C++, developed by Disney and CMU | panda3d | 2024-01-13 | 2013-09-30 | 539 | 7.678855 | https://avatars.githubusercontent.com/u/590956?v=4 | Powerful, mature open-source cross-platform game engine for Python and C++, developed by Disney and CMU | ['c-plus-plus', 'cross-platform', 'game-development', 'game-engine', 'gamedev', 'multi-platform', 'open-source', 'opengl', 'panda3d', 'panda3d-game-engine'] | ['c-plus-plus', 'cross-platform', 'game-development', 'game-engine', 'gamedev', 'multi-platform', 'open-source', 'opengl', 'panda3d', 'panda3d-game-engine'] | 2024-01-08 | [('pokepetter/ursina', 0.8077520132064819, 'gamedev', 2), ('kitao/pyxel', 0.6634293794631958, 'gamedev', 3), ('pygame/pygame', 0.609826922416687, 'gamedev', 2), ('lordmauve/pgzero', 0.5944162011146545, 'gamedev', 0), ('pythonarcade/arcade', 0.5839753746986389, 'gamedev', 1), ('pygamelib/pygamelib', 0.5582475662231445, ... | 162 | 1 | null | 5.98 | 71 | 28 | 125 | 0 | 1 | 2 | 1 | 71 | 121 | 90 | 1.7 | 46 |
1,154 | data | https://github.com/mongodb/mongo-python-driver | [] | null | [] | [] | null | null | null | mongodb/mongo-python-driver | mongo-python-driver | 3,982 | 1,192 | 240 | Python | https://pymongo.readthedocs.io | PyMongo - the Official MongoDB Python driver | mongodb | 2024-01-13 | 2009-01-15 | 784 | 5.074458 | https://avatars.githubusercontent.com/u/45120?v=4 | PyMongo - the Official MongoDB Python driver | ['mongodb', 'mongodb-driver', 'pymongo'] | ['mongodb', 'mongodb-driver', 'pymongo'] | 2024-01-12 | [('pyeve/eve', 0.5024893879890442, 'web', 1), ('mause/duckdb_engine', 0.5003612041473389, 'data', 0)] | 206 | 2 | null | 5.9 | 94 | 87 | 183 | 0 | 6 | 10 | 6 | 92 | 109 | 90 | 1.2 | 46 |
775 | diffusion | https://github.com/jina-ai/discoart | [] | null | [] | [] | null | null | null | jina-ai/discoart | discoart | 3,834 | 254 | 34 | Python | null | 🪩 Create Disco Diffusion artworks in one line | jina-ai | 2024-01-13 | 2022-06-30 | 82 | 46.352332 | https://avatars.githubusercontent.com/u/60539444?v=4 | 🪩 Create Disco Diffusion artworks in one line | ['clip-guided-diffusion', 'creative-ai', 'creative-art', 'cross-modal', 'dalle', 'diffusion', 'disco-diffusion', 'discodiffusion', 'generative-art', 'imgen', 'latent-diffusion', 'midjourney', 'multimodal', 'prompts', 'stable-diffusion'] | ['clip-guided-diffusion', 'creative-ai', 'creative-art', 'cross-modal', 'dalle', 'diffusion', 'disco-diffusion', 'discodiffusion', 'generative-art', 'imgen', 'latent-diffusion', 'midjourney', 'multimodal', 'prompts', 'stable-diffusion'] | 2023-05-16 | [('nateraw/stable-diffusion-videos', 0.5996933579444885, 'diffusion', 1), ('carson-katri/dream-textures', 0.5772116184234619, 'diffusion', 1), ('automatic1111/stable-diffusion-webui', 0.560263454914093, 'diffusion', 2), ('invoke-ai/invokeai', 0.55684894323349, 'diffusion', 3), ('compvis/stable-diffusion', 0.53159886598... | 7 | 2 | null | 0.06 | 2 | 2 | 19 | 8 | 1 | 77 | 1 | 2 | 3 | 90 | 1.5 | 46 |
692 | util | https://github.com/joblib/joblib | [] | null | [] | [] | null | null | null | joblib/joblib | joblib | 3,544 | 436 | 61 | Python | http://joblib.readthedocs.org | Computing with Python functions. | joblib | 2024-01-13 | 2010-05-07 | 716 | 4.945774 | https://avatars.githubusercontent.com/u/332661?v=4 | Computing with Python functions. | ['caching', 'memoization', 'multiprocessing', 'parallel-computing', 'threading'] | ['caching', 'memoization', 'multiprocessing', 'parallel-computing', 'threading'] | 2023-12-01 | [('dgilland/cacheout', 0.6794201135635376, 'perf', 2), ('python-cachier/cachier', 0.6731811165809631, 'perf', 2), ('noxdafox/pebble', 0.6440830826759338, 'perf', 2), ('ipython/ipyparallel', 0.6388868689537048, 'perf', 0), ('dask/dask', 0.6337271332740784, 'perf', 0), ('sumerc/yappi', 0.6218010783195496, 'profiling', 0)... | 127 | 6 | null | 1.27 | 46 | 21 | 167 | 1 | 3 | 6 | 3 | 46 | 103 | 90 | 2.2 | 46 |
419 | ml-rl | https://github.com/facebookresearch/reagent | [] | null | [] | [] | null | null | null | facebookresearch/reagent | ReAgent | 3,495 | 534 | 152 | Python | https://reagent.ai | A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.) | facebookresearch | 2024-01-14 | 2017-07-27 | 339 | 10.288057 | https://avatars.githubusercontent.com/u/16943930?v=4 | A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.) | [] | [] | 2024-01-09 | [('openai/gym', 0.573969841003418, 'ml-rl', 0), ('farama-foundation/gymnasium', 0.5644688606262207, 'ml-rl', 0), ('google/dopamine', 0.5503111481666565, 'ml-rl', 0), ('pettingzoo-team/pettingzoo', 0.5440720915794373, 'ml-rl', 0), ('deepmind/acme', 0.536990761756897, 'ml-rl', 0), ('thu-ml/tianshou', 0.5355173945426941, ... | 164 | 5 | null | 1.31 | 1 | 0 | 79 | 0 | 0 | 0 | 0 | 1 | 2 | 90 | 2 | 46 |
139 | ml-interpretability | https://github.com/pair-code/lit | [] | null | [] | [] | 1 | null | null | pair-code/lit | lit | 3,273 | 339 | 71 | TypeScript | https://pair-code.github.io/lit | The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface. | pair-code | 2024-01-14 | 2020-07-28 | 183 | 17.885246 | https://avatars.githubusercontent.com/u/29804435?v=4 | The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface. | ['machine-learning', 'natural-language-processing', 'visualization'] | ['machine-learning', 'natural-language-processing', 'visualization'] | 2023-11-08 | [('marcotcr/lime', 0.6946200132369995, 'ml-interpretability', 0), ('tensorflow/lucid', 0.6758688688278198, 'ml-interpretability', 2), ('csinva/imodels', 0.6702791452407837, 'ml', 1), ('seldonio/alibi', 0.6469577550888062, 'ml-interpretability', 1), ('eleutherai/pythia', 0.641786515712738, 'ml-interpretability', 0), ('m... | 34 | 3 | null | 5.25 | 34 | 16 | 42 | 2 | 2 | 3 | 2 | 33 | 13 | 90 | 0.4 | 46 |
1,200 | ml | https://github.com/huggingface/notebooks | [] | null | [] | [] | null | null | null | huggingface/notebooks | notebooks | 3,012 | 1,308 | 73 | Jupyter Notebook | null | Notebooks using the Hugging Face libraries 🤗 | huggingface | 2024-01-14 | 2020-06-15 | 189 | 15.924471 | https://avatars.githubusercontent.com/u/25720743?v=4 | Notebooks using the Hugging Face libraries 🤗 | [] | [] | 2024-01-05 | [('huggingface/huggingface_hub', 0.5788795948028564, 'ml', 0), ('koaning/calm-notebooks', 0.5623078942298889, 'study', 0), ('huggingface/diffusion-models-class', 0.5564571619033813, 'study', 0), ('cohere-ai/notebooks', 0.529309868812561, 'llm', 0)] | 75 | 1 | null | 4.69 | 35 | 12 | 44 | 0 | 0 | 0 | 0 | 35 | 49 | 90 | 1.4 | 46 |
1,717 | util | https://github.com/jendrikseipp/vulture | ['code-quality'] | null | [] | [] | null | null | null | jendrikseipp/vulture | vulture | 2,874 | 175 | 26 | Python | null | Find dead Python code | jendrikseipp | 2024-01-13 | 2017-03-06 | 360 | 7.980167 | null | Find dead Python code | ['dead-code-removal'] | ['code-quality', 'dead-code-removal'] | 2024-01-06 | [('facebookincubator/bowler', 0.5705008506774902, 'util', 0), ('dosisod/refurb', 0.5567197203636169, 'util', 0), ('rubik/radon', 0.5527566075325012, 'util', 0), ('agronholm/typeguard', 0.5461918711662292, 'typing', 1), ('google/yapf', 0.5393766164779663, 'util', 1), ('microsoft/pyright', 0.536612331867218, 'typing', 1)... | 40 | 4 | null | 0.62 | 17 | 10 | 84 | 0 | 4 | 7 | 4 | 17 | 29 | 90 | 1.7 | 46 |
99 | data | https://github.com/zoomeranalytics/xlwings | [] | null | [] | [] | null | null | null | zoomeranalytics/xlwings | xlwings | 2,773 | 482 | 122 | Python | https://www.xlwings.org | xlwings is a Python library that makes it easy to call Python from Excel and vice versa. It works with Excel on Windows and macOS as well as with Google Sheets and Excel on the web. | zoomeranalytics | 2024-01-13 | 2014-03-17 | 515 | 5.382973 | https://avatars.githubusercontent.com/u/6239016?v=4 | xlwings is a Python library that makes it easy to call Python from Excel and vice versa. It works with Excel on Windows and macOS as well as with Google Sheets and Excel on the web. | ['automation', 'excel', 'google-sheets', 'googlesheets', 'reporting'] | ['automation', 'excel', 'google-sheets', 'googlesheets', 'reporting'] | 2024-01-05 | [('jmcnamara/xlsxwriter', 0.7553142309188843, 'data', 0), ('jazzband/tablib', 0.5972012877464294, 'data', 0), ('connorferster/handcalcs', 0.5488008856773376, 'jupyter', 0), ('plotly/dash', 0.5458297729492188, 'viz', 0), ('tkrabel/bamboolib', 0.5089218616485596, 'pandas', 0)] | 64 | 2 | null | 3.02 | 47 | 27 | 120 | 0 | 17 | 16 | 17 | 48 | 84 | 90 | 1.8 | 46 |
1,437 | util | https://github.com/lxml/lxml | ['xml'] | null | [] | [] | null | null | null | lxml/lxml | lxml | 2,512 | 586 | 80 | Python | https://lxml.de/ | The lxml XML toolkit for Python | lxml | 2024-01-14 | 2011-02-11 | 676 | 3.712838 | https://avatars.githubusercontent.com/u/612230?v=4 | The lxml XML toolkit for Python | [] | ['xml'] | 2024-01-12 | [('roniemartinez/dude', 0.5113477110862732, 'util', 0)] | 156 | 5 | null | 5.48 | 19 | 16 | 157 | 0 | 9 | 11 | 9 | 19 | 26 | 90 | 1.4 | 46 |
1,067 | nlp | https://github.com/bigscience-workshop/promptsource | [] | null | [] | [] | null | null | null | bigscience-workshop/promptsource | promptsource | 2,325 | 320 | 28 | Python | null | Toolkit for creating, sharing and using natural language prompts. | bigscience-workshop | 2024-01-14 | 2021-05-19 | 140 | 16.506085 | https://avatars.githubusercontent.com/u/82455566?v=4 | Toolkit for creating, sharing and using natural language prompts. | ['machine-learning', 'natural-language-processing', 'nlp'] | ['machine-learning', 'natural-language-processing', 'nlp'] | 2023-10-23 | [('promptslab/awesome-prompt-engineering', 0.5903843641281128, 'study', 1), ('rasahq/rasa', 0.5880197882652283, 'llm', 3), ('promptslab/promptify', 0.5728100538253784, 'nlp', 2), ('srush/minichain', 0.5696084499359131, 'llm', 0), ('nltk/nltk', 0.5687624216079712, 'nlp', 3), ('gunthercox/chatterbot-corpus', 0.5633988976... | 65 | 6 | null | 0.13 | 11 | 11 | 32 | 3 | 0 | 2 | 2 | 11 | 10 | 90 | 0.9 | 46 |
1,367 | sim | https://github.com/rdkit/rdkit | ['chemistry'] | null | [] | [] | null | null | null | rdkit/rdkit | rdkit | 2,305 | 808 | 85 | HTML | null | The official sources for the RDKit library | rdkit | 2024-01-12 | 2013-05-12 | 559 | 4.121328 | https://avatars.githubusercontent.com/u/2018047?v=4 | The official sources for the RDKit library | ['c-plus-plus', 'cheminformatics', 'rdkit'] | ['c-plus-plus', 'cheminformatics', 'chemistry', 'rdkit'] | 2024-01-11 | [('espressomd/espresso', 0.5796418786048889, 'sim', 1), ('rasbt/machine-learning-book', 0.5607836246490479, 'study', 0), ('skorch-dev/skorch', 0.510020911693573, 'ml-dl', 0)] | 208 | 1 | null | 6.33 | 220 | 142 | 130 | 0 | 11 | 16 | 11 | 220 | 304 | 90 | 1.4 | 46 |
377 | ml-interpretability | https://github.com/oegedijk/explainerdashboard | [] | null | [] | [] | null | null | null | oegedijk/explainerdashboard | explainerdashboard | 2,123 | 305 | 22 | Python | http://explainerdashboard.readthedocs.io | Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models. | oegedijk | 2024-01-11 | 2019-10-30 | 221 | 9.569221 | null | Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models. | ['dash', 'dashboard', 'data-scientists', 'explainer', 'inner-workings', 'interactive-dashboards', 'interactive-plots', 'model-predictions', 'permutation-importances', 'plotly', 'shap', 'shap-values', 'xai', 'xai-library'] | ['dash', 'dashboard', 'data-scientists', 'explainer', 'inner-workings', 'interactive-dashboards', 'interactive-plots', 'model-predictions', 'permutation-importances', 'plotly', 'shap', 'shap-values', 'xai', 'xai-library'] | 2023-12-18 | [('interpretml/interpret', 0.6743864417076111, 'ml-interpretability', 1), ('xplainable/xplainable', 0.627983570098877, 'ml-interpretability', 2), ('seldonio/alibi', 0.6191368699073792, 'ml-interpretability', 1), ('teamhg-memex/eli5', 0.602367103099823, 'ml', 0), ('polyaxon/datatile', 0.5954424142837524, 'pandas', 1), (... | 21 | 6 | null | 1.04 | 14 | 5 | 51 | 1 | 6 | 19 | 6 | 14 | 22 | 90 | 1.6 | 46 |
1,136 | util | https://github.com/libaudioflux/audioflux | [] | null | [] | [] | null | null | null | libaudioflux/audioflux | audioFlux | 1,957 | 95 | 26 | C | https://audioflux.top | A library for audio and music analysis, feature extraction. | libaudioflux | 2024-01-13 | 2023-01-16 | 54 | 36.145119 | https://avatars.githubusercontent.com/u/105165315?v=4 | A library for audio and music analysis, feature extraction. | ['audio', 'audio-analysis', 'audio-features', 'audio-processing', 'deep-learning', 'machine-learning', 'mfcc', 'mir', 'music', 'music-analysis', 'music-information-retrieval', 'pitch', 'signal-processing', 'spectral-analysis', 'spectrogram', 'time-frequency-analysis', 'wavelet-analysis', 'wavelet-transform'] | ['audio', 'audio-analysis', 'audio-features', 'audio-processing', 'deep-learning', 'machine-learning', 'mfcc', 'mir', 'music', 'music-analysis', 'music-information-retrieval', 'pitch', 'signal-processing', 'spectral-analysis', 'spectrogram', 'time-frequency-analysis', 'wavelet-analysis', 'wavelet-transform'] | 2023-12-22 | [('bastibe/python-soundfile', 0.6440500617027283, 'util', 0), ('spotify/pedalboard', 0.5974409580230713, 'util', 2), ('facebookresearch/audiocraft', 0.551815927028656, 'util', 1), ('speechbrain/speechbrain', 0.5162292718887329, 'nlp', 3), ('quodlibet/mutagen', 0.5058978796005249, 'util', 1)] | 5 | 1 | null | 1.33 | 6 | 3 | 12 | 1 | 8 | 8 | 8 | 6 | 4 | 90 | 0.7 | 46 |
955 | gis | https://github.com/azavea/raster-vision | [] | null | [] | [] | null | null | null | azavea/raster-vision | raster-vision | 1,956 | 374 | 74 | Python | https://docs.rastervision.io | An open source library and framework for deep learning on satellite and aerial imagery. | azavea | 2024-01-11 | 2017-02-02 | 364 | 5.363102 | https://avatars.githubusercontent.com/u/595231?v=4 | An open source library and framework for deep learning on satellite and aerial imagery. | ['classification', 'computer-vision', 'deep-learning', 'geospatial', 'machine-learning', 'object-detection', 'pytorch', 'remote-sensing', 'semantic-segmentation'] | ['classification', 'computer-vision', 'deep-learning', 'geospatial', 'machine-learning', 'object-detection', 'pytorch', 'remote-sensing', 'semantic-segmentation'] | 2024-01-11 | [('datasystemslab/geotorch', 0.6860873103141785, 'gis', 1), ('developmentseed/label-maker', 0.6791407465934753, 'gis', 3), ('microsoft/torchgeo', 0.6176372766494751, 'gis', 5), ('remotesensinglab/raster4ml', 0.5898652076721191, 'gis', 2), ('tensorflow/tensorflow', 0.5648720860481262, 'ml-dl', 2), ('deci-ai/super-gradie... | 35 | 5 | null | 4.73 | 77 | 56 | 85 | 0 | 6 | 3 | 6 | 77 | 80 | 90 | 1 | 46 |
940 | nlp | https://github.com/alibaba/easynlp | [] | null | [] | [] | null | null | null | alibaba/easynlp | EasyNLP | 1,872 | 238 | 37 | Python | null | EasyNLP: A Comprehensive and Easy-to-use NLP Toolkit | alibaba | 2024-01-13 | 2022-04-06 | 94 | 19.73494 | https://avatars.githubusercontent.com/u/1961952?v=4 | EasyNLP: A Comprehensive and Easy-to-use NLP Toolkit | ['bert', 'deep-learning', 'fewshot-learning', 'knowledge-distillation', 'knowledge-pretraining', 'machine-learning', 'nlp', 'pretrained-models', 'pytorch', 'text-classification', 'text-image-retrieval', 'text-to-image-synthesis', 'transfer-learning', 'transformers'] | ['bert', 'deep-learning', 'fewshot-learning', 'knowledge-distillation', 'knowledge-pretraining', 'machine-learning', 'nlp', 'pretrained-models', 'pytorch', 'text-classification', 'text-image-retrieval', 'text-to-image-synthesis', 'transfer-learning', 'transformers'] | 2024-01-10 | [('allenai/allennlp', 0.6890572309494019, 'nlp', 3), ('paddlepaddle/paddlenlp', 0.6783795952796936, 'llm', 4), ('graykode/nlp-tutorial', 0.6614455580711365, 'study', 3), ('huggingface/transformers', 0.6499559879302979, 'nlp', 6), ('deepset-ai/farm', 0.6495715975761414, 'nlp', 6), ('norskregnesentral/skweak', 0.63387173... | 39 | 5 | null | 1.33 | 11 | 5 | 22 | 0 | 0 | 1 | 1 | 11 | 4 | 90 | 0.4 | 46 |
1,135 | math | https://github.com/pyomo/pyomo | [] | null | [] | [] | null | null | null | pyomo/pyomo | pyomo | 1,749 | 479 | 61 | Python | https://www.pyomo.org | An object-oriented algebraic modeling language in Python for structured optimization problems. | pyomo | 2024-01-12 | 2016-05-27 | 400 | 4.366262 | https://avatars.githubusercontent.com/u/10505959?v=4 | An object-oriented algebraic modeling language in Python for structured optimization problems. | ['linear-programming', 'mathematical-programming', 'modeling-language', 'nonlinear-programming', 'optimization'] | ['linear-programming', 'mathematical-programming', 'modeling-language', 'nonlinear-programming', 'optimization'] | 2024-01-13 | [('sympy/sympy', 0.5923652052879333, 'math', 0), ('keon/algorithms', 0.5572477579116821, 'util', 0), ('google/pyglove', 0.5334599018096924, 'util', 0), ('scikit-optimize/scikit-optimize', 0.5328642129898071, 'ml', 1), ('pyston/pyston', 0.5302437543869019, 'util', 0), ('pytoolz/toolz', 0.5213468670845032, 'util', 0), ('... | 137 | 1 | null | 48.38 | 186 | 132 | 93 | 0 | 5 | 8 | 5 | 186 | 238 | 90 | 1.3 | 46 |
660 | ml | https://github.com/huggingface/evaluate | [] | null | [] | [] | null | null | null | huggingface/evaluate | evaluate | 1,673 | 206 | 48 | Python | https://huggingface.co/docs/evaluate | 🤗 Evaluate: A library for easily evaluating machine learning models and datasets. | huggingface | 2024-01-13 | 2022-03-30 | 95 | 17.453055 | https://avatars.githubusercontent.com/u/25720743?v=4 | 🤗 Evaluate: A library for easily evaluating machine learning models and datasets. | ['evaluation', 'machine-learning'] | ['evaluation', 'machine-learning'] | 2023-12-27 | [('tensorflow/data-validation', 0.7562239170074463, 'ml-ops', 0), ('anthropics/evals', 0.7150794267654419, 'llm', 0), ('teamhg-memex/eli5', 0.6364562511444092, 'ml', 1), ('districtdatalabs/yellowbrick', 0.6335552334785461, 'ml', 1), ('rasbt/mlxtend', 0.6174339056015015, 'ml', 1), ('eugeneyan/testing-ml', 0.616701126098... | 124 | 3 | null | 0.46 | 51 | 12 | 22 | 1 | 1 | 5 | 1 | 51 | 51 | 90 | 1 | 46 |
853 | jupyter | https://github.com/jupyter/nbconvert | [] | null | [] | [] | null | null | null | jupyter/nbconvert | nbconvert | 1,610 | 547 | 51 | Python | https://nbconvert.readthedocs.io/ | Jupyter Notebook Conversion | jupyter | 2024-01-12 | 2015-04-09 | 459 | 3.502175 | https://avatars.githubusercontent.com/u/7388996?v=4 | Jupyter Notebook Conversion | [] | [] | 2024-01-11 | [('jupyter/nbformat', 0.810336709022522, 'jupyter', 0), ('jupyter/notebook', 0.7077092528343201, 'jupyter', 0), ('jupyterlab/jupyterlab-desktop', 0.6312793493270874, 'jupyter', 0), ('jupyter/nbgrader', 0.6126564145088196, 'jupyter', 0), ('cohere-ai/notebooks', 0.6110220551490784, 'llm', 0), ('jupyter-widgets/ipywidgets... | 270 | 7 | null | 1.9 | 67 | 31 | 107 | 0 | 24 | 10 | 24 | 67 | 63 | 90 | 0.9 | 46 |
1,076 | ml | https://github.com/kubeflow/katib | [] | null | [] | [] | null | null | null | kubeflow/katib | katib | 1,391 | 394 | 67 | Go | null | Repository for hyperparameter tuning | kubeflow | 2024-01-13 | 2018-04-03 | 304 | 4.575658 | https://avatars.githubusercontent.com/u/33164907?v=4 | Repository for hyperparameter tuning | [] | [] | 2024-01-09 | [('optuna/optuna', 0.6405646800994873, 'ml', 0), ('ray-project/tune-sklearn', 0.626979410648346, 'ml', 0), ('microsoft/flaml', 0.6054434776306152, 'ml', 0), ('hyperopt/hyperopt', 0.6022725701332092, 'ml', 0), ('determined-ai/determined', 0.5883219242095947, 'ml-ops', 0), ('google/vizier', 0.5503707528114319, 'ml', 0), ... | 111 | 7 | null | 1.79 | 53 | 26 | 70 | 0 | 2 | 4 | 2 | 53 | 125 | 90 | 2.4 | 46 |
926 | nlp | https://github.com/jonasgeiping/cramming | [] | null | [] | [] | null | null | null | jonasgeiping/cramming | cramming | 1,191 | 90 | 21 | Python | null | Cramming the training of a (BERT-type) language model into limited compute. | jonasgeiping | 2024-01-11 | 2022-12-29 | 56 | 21 | null | Cramming the training of a (BERT-type) language model into limited compute. | ['english-language', 'language-model', 'machine-learning'] | ['english-language', 'language-model', 'machine-learning'] | 2023-09-03 | [('bigscience-workshop/megatron-deepspeed', 0.6582860946655273, 'llm', 0), ('microsoft/megatron-deepspeed', 0.6582860946655273, 'llm', 0), ('extreme-bert/extreme-bert', 0.6568642258644104, 'llm', 2), ('deepset-ai/farm', 0.6375002861022949, 'nlp', 0), ('ai21labs/lm-evaluation', 0.6214629411697388, 'llm', 1), ('reasoning... | 7 | 3 | null | 1.08 | 6 | 6 | 13 | 4 | 2 | 2 | 2 | 6 | 20 | 90 | 3.3 | 46 |
1,266 | perf | https://github.com/intel/intel-extension-for-pytorch | [] | null | [] | [] | null | null | null | intel/intel-extension-for-pytorch | intel-extension-for-pytorch | 1,150 | 167 | 34 | Python | null | A Python package for extending the official PyTorch that can easily obtain performance on Intel platform | intel | 2024-01-14 | 2020-04-15 | 197 | 5.812274 | https://avatars.githubusercontent.com/u/17888862?v=4 | A Python package for extending the official PyTorch that can easily obtain performance on Intel platform | ['deep-learning', 'intel', 'machine-learning', 'neural-network', 'pytorch', 'quantization'] | ['deep-learning', 'intel', 'machine-learning', 'neural-network', 'pytorch', 'quantization'] | 2024-01-11 | [('pytorch/ignite', 0.7741976380348206, 'ml-dl', 4), ('skorch-dev/skorch', 0.7512941360473633, 'ml-dl', 2), ('rasbt/machine-learning-book', 0.7345353960990906, 'study', 3), ('nvidia/apex', 0.7110769152641296, 'ml-dl', 0), ('karpathy/micrograd', 0.6794243454933167, 'study', 0), ('pytorch/data', 0.6773589849472046, 'data... | 60 | 2 | null | 8.48 | 101 | 24 | 46 | 0 | 8 | 9 | 8 | 101 | 198 | 90 | 2 | 46 |
694 | perf | https://github.com/intel/scikit-learn-intelex | [] | null | [] | [] | null | null | null | intel/scikit-learn-intelex | scikit-learn-intelex | 1,105 | 167 | 30 | Python | https://intel.github.io/scikit-learn-intelex/ | Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application | intel | 2024-01-12 | 2018-08-07 | 286 | 3.863636 | https://avatars.githubusercontent.com/u/17888862?v=4 | Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application | ['ai-inference', 'ai-machine-learning', 'ai-training', 'analytics', 'big-data', 'data-analysis', 'gpu', 'intel', 'machine-learning', 'machine-learning-algorithms', 'oneapi', 'scikit-learn', 'swrepo'] | ['ai-inference', 'ai-machine-learning', 'ai-training', 'analytics', 'big-data', 'data-analysis', 'gpu', 'intel', 'machine-learning', 'machine-learning-algorithms', 'oneapi', 'scikit-learn', 'swrepo'] | 2024-01-11 | [('intel/intel-extension-for-pytorch', 0.6315147280693054, 'perf', 2), ('automl/auto-sklearn', 0.5883508920669556, 'ml', 1), ('iryna-kondr/scikit-llm', 0.5876615047454834, 'llm', 2), ('koaning/human-learn', 0.5819746255874634, 'data', 2), ('skops-dev/skops', 0.5795713067054749, 'ml-ops', 2), ('microsoft/onnxruntime', 0... | 77 | 2 | null | 5.44 | 136 | 105 | 66 | 0 | 6 | 5 | 6 | 136 | 532 | 90 | 3.9 | 46 |
1,727 | llm | https://github.com/truera/trulens | ['evaluation'] | null | [] | [] | null | null | null | truera/trulens | trulens | 1,042 | 83 | 12 | Jupyter Notebook | https://www.trulens.org/ | Evaluation and Tracking for LLM Experiments | truera | 2024-01-13 | 2020-11-02 | 169 | 6.160473 | https://avatars.githubusercontent.com/u/51224128?v=4 | Evaluation and Tracking for LLM Experiments | ['explainable-ml', 'llm', 'llmops', 'machine-learning', 'neural-networks'] | ['evaluation', 'explainable-ml', 'llm', 'llmops', 'machine-learning', 'neural-networks'] | 2024-01-12 | [('bentoml/openllm', 0.5837077498435974, 'ml-ops', 2), ('vllm-project/vllm', 0.5575326681137085, 'llm', 2), ('citadel-ai/langcheck', 0.5569631457328796, 'llm', 1), ('microsoft/jarvis', 0.5391638278961182, 'llm', 0), ('arize-ai/phoenix', 0.532617449760437, 'ml-interpretability', 1), ('wandb/client', 0.5260670185089111, ... | 32 | 1 | null | 10.73 | 306 | 286 | 39 | 0 | 23 | 10 | 23 | 306 | 461 | 90 | 1.5 | 46 |
1,893 | util | https://github.com/ofek/pyapp | ['installer', 'bundle', 'packaging'] | null | [] | [] | null | null | null | ofek/pyapp | pyapp | 883 | 17 | 6 | Rust | https://ofek.dev/pyapp/ | Runtime installer for Python applications | ofek | 2024-01-13 | 2023-05-07 | 38 | 23.063433 | null | Runtime installer for Python applications | ['application', 'build', 'cli', 'packaging', 'rust'] | ['application', 'build', 'bundle', 'cli', 'installer', 'packaging', 'rust'] | 2024-01-01 | [('pyodide/micropip', 0.6668835282325745, 'util', 0), ('beeware/briefcase', 0.6602802276611328, 'util', 1), ('indygreg/pyoxidizer', 0.6547517776489258, 'util', 1), ('pypa/hatch', 0.6210417747497559, 'util', 3), ('pypa/pipx', 0.604620099067688, 'util', 1), ('pyinstaller/pyinstaller', 0.5914837121963501, 'util', 1), ('mi... | 5 | 1 | null | 1.75 | 21 | 11 | 8 | 0 | 15 | 23 | 15 | 21 | 24 | 90 | 1.1 | 46 |
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