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# --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.5' # jupytext_version: 1.14.4 # kernelspec: # display_name: conda_python2 # language: python # name: conda_python2 # --- # # Feature processing with Spark, training...
advanced_functionality/inference_pipeline_sparkml_xgboost_abalone/inference_pipeline_sparkml_xgboost_abalone.ipynb
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prototyping/auto-segmentation/sb/00-stage-0-prototyping/01-mask-with-edge-falloff.ipynb
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notebooks/train_test_validation_splits.ipynb
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NEWS-AGGRIGATOR DATASET.ipynb
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examples/camera_manipulation.ipynb
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Wines.ipynb
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notebooks/1. Analysis/samples/2 - Analizando dataset nuevo DM_RETAIL_CLIE.ipynb
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Misc/xml_data/xml_blockcorpus.ipynb
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In Progress - Deep Learning - The Straight Dope/02 - Introduction to Supervised Learning/04 - Multiclass logistic regression from scratch.ipynb
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Weather Analysis/Climate Type Determination.ipynb
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notebooks/7_TDEM_Permeability.ipynb
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content/downloads/notebooks/udacity/deep_learning_foundations_nanodegree/project_2_notes_convolutional_neural_networks.ipynb
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Datasets.ipynb
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final/notebooks/scratch/id3-from-scratch.ipynb
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数据挖掘与数据仓库/实验三/.ipynb_checkpoints/实验三相关度高的特征子集-checkpoint.ipynb
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ex03/Guilherme_Pereira/Aula_3_Guilherme_Pereira.ipynb
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notebooks/Halide Target.ipynb
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test_model.ipynb
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notebooks/AM_prepareData.ipynb
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notebooks/01-au-feature-engineering-playground.ipynb
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presentation.ipynb
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image-multi-class-weights.ipynb
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Calculator.ipynb
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notebooks/dask_4D_LLSM.ipynb
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age prediction.ipynb
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Ejercicio_Matriz_4x4.ipynb
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1. Python Introductory Course/1. Intro to Python/Dictionaries.ipynb
# -*- coding: utf-8 -*- # --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.5' # jupytext_version: 1.14.4 # kernelspec: # display_name: Q# # language: qsharp # name: iqsharp # --- # # Multi-Qubit Systems # # This tut...
tutorials/MultiQubitSystems/MultiQubitSystems.ipynb
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tutorial/How-to-launch-jupyter-notebook-from-cluster/How.ipynb
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notebooks/20210711-load-sp500-data.ipynb
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augmentations_test.ipynb
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cleaning.ipynb
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Application_2.ipynb
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Data Analysis.ipynb
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fig1.ipynb
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Ocean_IA_Deep_14_08_19.ipynb
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05-recommender/01-factorization-machine.ipynb
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FaceNet-distributed-training/pipeline/k8s_distributed_training_final_version.ipynb
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(2) [Jupyter - Youth] Module 5.ipynb
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work/long_period/gmo/default/tutorial.ipynb
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2.substitution-cipher/substitution_cipher.ipynb
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notebooks/train_classification_model.ipynb
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15_methodes_chaines.ipynb
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skdaccess/examples/Demo_GLDAS.ipynb
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courses/8. Datasets exploration in Python.ipynb
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day2_visualization.ipynb
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notebook/US immigration.ipynb
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nbs/Uniprot_integration.ipynb
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compLingProject104SentenceAlignmentHunalignV04a.ipynb
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Chapter11/Activity11.02/Activity11_02.ipynb
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content/lessons/06/Class-Coding-Lab/CCL-Functions.ipynb
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notebooks/2-linear-algebra-ii.ipynb
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Final Notebook/soccerAnalysis.ipynb
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experiments/sphere-cef-joint.ipynb
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examples/voxel_edit.ipynb
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HAR_FNOW.ipynb
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dataset/data_augmentation.ipynb
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Convergence_analysis.ipynb
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Codes/Transfer Learning/Simulated-To-Physical-Cross-System/.ipynb_checkpoints/All_Models_Sim_to_PHY-checkpoint.ipynb
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notebooks/tutorials/overland_flow/overland_flow_driver.ipynb
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notebooks/FiniteDifferences1D.ipynb
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DS-Unit-1-Sprint-1-Dealing-With-Data-master/module4-makefeatures/LS_DS_114_Make_Features_Assignment.ipynb
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xunfei_tts.ipynb
# --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.5' # jupytext_version: 1.14.4 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # # Chained Visualizations with Yellowbrick Pipelines ...
examples/rebeccabilbro/pipelines.ipynb
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eda/visualisation.ipynb
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dalbem.ipynb
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Transfer Learning with Convolutional Neural Networks - Dificultad media/Transfer Learning with Convolutional Neural Networks - CIFAR10 - Primera parte.ipynb
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5-mapping-duplicate-municipals.ipynb
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02 - Disaster Response Pipelines/notebooks/ML Pipeline Preparation.ipynb
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Team Assignments/test.ipynb
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notebooks/CustomerScenarios/Case Study - Recommendation AB Testing at An Online Travel Company.ipynb
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Data/ConvertCAIC.ipynb
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DeepLearningFrameworks/inference/ResNet50-MXNet-mkl.ipynb
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linear-regression.ipynb
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3. Spark Basics.ipynb
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learning-pytorch-2-new-autograd-functions.ipynb
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Final_Exam.ipynb
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cardio/models/fft_model/fft_model_training.ipynb
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notebooks/prepare_nei_data.ipynb
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03_DataVisualization/02_FormattingPlots.ipynb
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site/normal-demonstration.ipynb
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tutorial/notebooks/nonspinning_nr_emri.ipynb
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forcing/scavenging---euphotic-depth.ipynb
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OpenClassRoom/RidgeAndLassoRegression/RidgeAndLassoRegression.ipynb
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notebooks/Neural_Machine_Translation_Example.ipynb
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inclass/inclass3-abpwrs/notes/20190402_ClassNotes.ipynb
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legacy/unidad_1/04_OOP_model.ipynb
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Untitled20.ipynb
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TASK 1- Iris Flowers Classification/TASK 1 - Iris Flowers Classification.ipynb
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hello_py.ipynb
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Untitled1.ipynb
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unsupervised-summarization/1.skip-thought.ipynb
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ConditionalDensityEstimationTutorial.ipynb
# --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.5' # jupytext_version: 1.14.4 # --- # # Analyize Google Chrome history # # Idea and initial code taken from the [Analyzing Browser History Using Python and Pandas](https://applec...
analyze_chrome_history.ipynb
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Scraping/whiskey_Scraper.ipynb
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notebook/20161124_panels.ipynb
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scratch/scratch.ipynb
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.ipynb_checkpoints/Minneapolis Weather-checkpoint.ipynb
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main.ipynb
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examples/notebooks/unet_segmentation_3d_ignite.ipynb