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jupyter/keras-model.ipynb
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Model backlog/Deep Learning/[2nd] Bi LSTM - Baseline.ipynb
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Harshitha/Copy of Complex_Assignement_harshitha.ipynb
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site/en/r2/tutorials/keras/save_and_restore_models.ipynb
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Day 3/01 - Multilayer Perceptron [MLP].ipynb
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notebooks/data_preprocessing.ipynb
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scrape_mars.ipynb
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milestone3/Milestone3-Task4.ipynb
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MLGame/games/snake/ml/others/train.py_ian.ipynb
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pandas_plot.ipynb
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miniprojectsem4/.ipynb_checkpoints/prac-checkpoint.ipynb
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JpytrNb/jupyter/Gas-z-A2(MatchData).ipynb
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TensorFlow-2.0/04-CNN/Untitled.ipynb
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NumPy/100_Numpy_exercises_with_hint.ipynb
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docs/how_tos/create_custom_quantum_feature_map.ipynb
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Experiments/HateSpeechDetectionModels/otherExperiments/DNN/Offensive2020-SharedTask/Try and error Experiments/Copy of text_classification_Keras_HS_offiensive2020.ipynb
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logistic-regression.ipynb
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simulations/quadrupole.ipynb
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scikit/Chapter 7/Text Data Motivation.ipynb
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labs/simulation/lab4/sim_lab4_nspp_STUDENT.ipynb
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notebooks/11_Process_synchronization.ipynb
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docs/jax-101/03-vectorization.ipynb
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notebooks/lab-08.ipynb
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examples/example-1.1-custom-parameter-exploration.ipynb
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Sprint challenge/Jean Fraga DS_Unit_1_Sprint_Challenge_3_(2).ipynb
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07-module-feature-monitoring/m7_nb1_feature_monitoring.ipynb
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kap5.ipynb
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13_loading_and_preprocessing_data.ipynb
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Proyectos-guia/Lyrics-Generation-using-BERT-master/code/bert_baselines.ipynb
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1_1_Image_Representation/2. Visualizing RGB Channels.ipynb
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11. Train and evaluate multiclass classification models.ipynb
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index.ipynb
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notebooks/helm_examples.ipynb
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Jupyter/M09-Optional/SIT742P02B-StructuredDataNumPy.ipynb
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radar_chart.ipynb
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NER_BERT.ipynb
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notebooks/Clean_gold/Clean_v3.ipynb
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0.12/_downloads/plot_read_bem_surfaces.ipynb
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Chapter_05_if_for_while.ipynb
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Automatic image-based segmentation of the heart from CT scans.ipynb
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tensorflow/lite/g3doc/tutorials/model_maker_image_classification.ipynb
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Untitled.ipynb
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notebooks/ch6.ipynb
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Tarea8.ipynb
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00_why_python.ipynb
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provenance_lib/notebooks/zf_to_metadata_df.ipynb
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scripts/notebook-python-spark.ipynb
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master/0_index.ipynb
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vehicle_control/trajectory_generation.ipynb
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JupyterNotebooks/Labs/Lab 5.ipynb
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code/1.4.3_Content_Filtering_Fullmatrix_pred.ipynb
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tests-Copy1.ipynb
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final_project/Untitled.ipynb
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notebooks/Multivariate-Linear-Regression.ipynb
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01_Workshop-master/Chapter05/Keyword Arguments.ipynb
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docs/examples/containers.ipynb
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tensorflow_model/archive/Daylight_Autonomy_Array.ipynb
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notebooks/001-datastructures.ipynb
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code/02-exploring_fmriprep.ipynb
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PythonNumpy2DArrays.ipynb
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Data Science and Machine Learning/Introduction to ML Notebooks/Introduction to ML with Python (UCI)/Lecture-19-Stochastic-Gradient-Descent.ipynb
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convert-delta.ipynb
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sentiment-network/Sentiment_Classification_Projects.ipynb
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case3-iris_data/basic.ipynb
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Day08.ipynb
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numpy-neural-networks.ipynb
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zufall/mat/aufgaben18.ipynb
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FannieMae_credit_ risk_Champion-Challenger.ipynb
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notebooks/classifier/Tribuo Classifier.ipynb
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examples/metocean/JONSWAP.ipynb
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docs/optcutfreq.ipynb
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notebooks/Reanalysis over Portland.ipynb
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science/notebook/matplot-animation.ipynb
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src/jupyter_contrib_nbextensions/TestFiles/Control_Unordered Notebook.ipynb
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Smart_Home.ipynb
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notebooks/qmctorch.ipynb
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tsa/jose/08_General Forecasting Models/64_ARIMA.ipynb
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daily/20191023.ipynb
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notebooks/tensorflow/train-mnist-distributed.ipynb
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Untitled.ipynb
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geoloc.ipynb
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Starter_Code.ipynb
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notebooks/checks/layerless_check.ipynb
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genesCuration/monte-carlo/extract-gene-sets.ipynb
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Hold_Me_Tight.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 # --- # ![hercules](img/Hercules_sesame.jpg) # # Python & h...
sesame/starter.ipynb
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Day 4/alaroabubakarolayemi@yahoo.com(Matplotlib Task).ipynb
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3_ML_Regressao_Custos_Seguro_Saude.ipynb
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Rethinking/end-of-chapter-practice-problems/ch-12.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 # --- # # Smart Queue Monitoring System - Retail Scenario # ...
Retail_Scenario.ipynb
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src/preprocess/preprocess_for_geodatabase.ipynb
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static/notebooks/eg-serving-malware.ipynb
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Vectorize.ipynb
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model_structures/gender identification/data.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 # --- # # Settings # %env TF_KERAS = 1 import os sep_local ...
notebooks/Super_Resolution/denoising/Upsampling/ellwlb/CBSD68/CBSD68_Pre-Upsampling_Convolutional.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 # --- # **Neural networks for road segmentation** # ========...
homework02/homework-part1-segmentation.ipynb
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cs224w/yes_gd_rbf.ipynb
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007 - Batches.ipynb
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code/mnist_04_cnn.ipynb
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3.Q_Mean_W2V.ipynb