├── .github └── workflows │ ├── BuildImages.yml │ ├── bind_server_release.yml │ └── binder.yml ├── Artifacts.toml ├── CondaPkg.toml ├── Dockerfile ├── LICENSE.md ├── Manifest.toml ├── Project.toml ├── README.md ├── RLEnv ├── Manifest.toml └── Project.toml ├── data ├── corpus │ ├── da.txt │ ├── en.txt │ ├── es.txt │ ├── fr.txt │ └── it.txt ├── spam.csv ├── spam_preprocessed.csv ├── spam_preprocessed_test.csv ├── weather2015-2018.csv └── weather2019-2020.csv ├── extras ├── generative_models.jl └── transfer_learning.jl ├── index.jl ├── notebooks ├── clustering.jl ├── figures │ ├── biplot_exercise.png │ ├── carrace.png │ ├── conv_exercise.png │ ├── dropout.png │ ├── lr.png │ ├── lr_heteroscedastic.png │ ├── mnist_example1.png │ ├── mnist_kmeans.png │ ├── mnist_kmeans_table.png │ ├── mnist_pca.png │ ├── mnist_tsne.png │ ├── mnist_umap.png │ ├── mountaincar.png │ ├── overparametrized.png │ ├── pca1.png │ ├── pca2.png │ ├── poly.png │ ├── trees3.png │ ├── weather_mlp.png │ └── weather_mlp_normal.png ├── flexibility.jl ├── generalized_linear_regression.jl ├── gradient_descent.jl ├── introduction.jl ├── mlp.jl ├── model_evaluation.jl ├── neuralnet.jl ├── other_nonlinear.jl ├── pca.jl ├── regularization.jl ├── rl.jl ├── rnn.jl ├── supervised_learning.jl └── transformations.jl ├── precompile └── warmup.jl ├── scripts ├── preprocess_spam.jl ├── preprocess_weather.jl └── wordcloud.jl ├── slides ├── 01-introduction.pdf ├── 02-supervised_learning.pdf ├── 03-generalized_linear_regression.pdf ├── 04-flexibility_and_bias_variance_decomposition.pdf ├── 05-model_assessment.pdf ├── 06-regularization.pdf ├── 07-feature_engineering.pdf ├── 08-gradient_descent.pdf ├── 09-multi_layer_perceptron.pdf ├── 10-other_nonlinear_methods.pdf ├── 11-clustering.pdf ├── 12-principal_component_analysis.pdf ├── 13-generative_models.pdf └── 14-reinforcement_learning.pdf └── src ├── MLCourse.jl └── notebooks.jl /.github/workflows/BuildImages.yml: 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