├── .gitignore ├── Exercises ├── 00_neural_nets_breakout.ipynb ├── bayesian_breakout_00.ipynb ├── bayesian_breakout_01.ipynb ├── breakout_1_pandas.ipynb ├── classification_breakout_00.ipynb ├── data │ └── SFHousing.csv ├── data_BirthRate.txt └── regression_breakout_00.ipynb ├── LICENSE ├── Lectures ├── 1_ComputationalAndInferentialThinking │ ├── 00_introduction.ipynb │ ├── 01_ds_ml_stat.ipynb │ ├── 02_Exploration_and_Viz.ipynb │ ├── 02a_matplotlib_and_seaborn.ipynb │ ├── 02b_3D_plotting.ipynb │ ├── 03_Featurization_and_NLP.ipynb │ ├── data │ │ ├── stained_glass_barcelona.jpg │ │ └── stations.txt │ ├── imgs │ │ ├── bias_var.png │ │ ├── feat.png │ │ ├── feature.png │ │ ├── feature2.png │ │ ├── image176.tif │ │ ├── josh_observatorio.png │ │ ├── jsb1.png │ │ ├── learn_types.png │ │ ├── my_data_file.jpg │ │ ├── my_data_file.npy │ │ ├── pipe.png │ │ ├── skeptic.png │ │ ├── term.png │ │ ├── three.png │ │ └── workflow.png │ └── transform.py ├── 2_BayesianInference │ ├── 00_Bayesian_Inference.ipynb │ ├── 01_MCMC_introduction.ipynb │ ├── 02_hierarchical_example_checking_convergence.ipynb │ ├── 03_Gaussian_Processes.ipynb │ └── imgs │ │ ├── bayes.png │ │ ├── gp.png │ │ ├── ma.png │ │ ├── ma1.png │ │ ├── mining.png │ │ ├── mining1.png │ │ ├── rsta20110550f02.jpg │ │ └── rsta20110550f03.jpg ├── 3_SupervisedLearning │ ├── 00_Supervised_Learning_regression.ipynb │ ├── 01_Classification_I.ipynb │ └── 02_Classification_II.ipynb ├── 4_NeuralNetworksIntroduction │ ├── 00_neural_networks_introduction.ipynb │ ├── 01_neural_nets_with_keras.ipynb │ ├── 01a_classification_with_keras.ipynb │ ├── draw_nn.py │ └── tensorboard.ipynb ├── 5_DeepConvNets │ ├── 00_convnets.ipynb │ ├── 01_Learning_on_Sequences.ipynb │ ├── reproduce.py │ └── tensorboard.ipynb ├── 6_GenerativeAndCompressiveModels │ ├── 00_autoencoders.ipynb │ ├── 01_GenerativeAdversarialNetworks.ipynb │ ├── imgs │ │ ├── faces.png │ │ ├── fashion.png │ │ ├── gans.png │ │ └── super.png │ └── nn_results │ │ └── colombia_vae_cnn_fashion_70.h5 ├── 7_SelfSupervisedAndAnomalies │ ├── 00_clustering.ipynb │ ├── 01_anomaly_detection.ipynb │ ├── 02_transfer_learning.ipynb │ ├── 03_hyperparameter_optimization.ipynb │ ├── imgs │ │ └── German_Shepherd.jpg │ └── merged_dataset_BearingTest_2.csv ├── 8_RealWorldML │ ├── 00_introduction.ipynb │ ├── 01_bias_ethics.ipynb │ ├── 02_wrapping_up.ipynb │ └── imgs │ │ ├── bias.png │ │ ├── ethical.png │ │ ├── flaws.png │ │ ├── frameworks.png │ │ ├── impl.png │ │ ├── interp.png │ │ ├── linops.png │ │ ├── medical.png │ │ ├── optim.png │ │ ├── roc.png │ │ ├── scully.png │ │ ├── strata-1.mov │ │ ├── tesla.png │ │ ├── ucb_drive.png │ │ └── weak.png └── talktools.py ├── README.md ├── apt.txt ├── environment.yml └── postBuild /.gitignore: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/profjsb/ml_course/HEAD/.gitignore -------------------------------------------------------------------------------- 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