├── Chapter01 ├── cross_validation.py ├── cross_validation_2.py └── cross_validation_3.py ├── Chapter02 ├── cple.py ├── generative_gaussian_mixtures.py ├── s3vm.py └── tsvm.py ├── Chapter03 ├── Old │ └── label_spreading.py ├── isomap.py ├── label_propagation.py ├── label_propagation_mrw.py ├── label_propagation_scikit_learn.py ├── label_spreading.py ├── laplacian_spectral_embedding.py ├── locally_linear_embedding.py └── tsne.py ├── Chapter04 ├── direct_sampling.py ├── hmm.py ├── metropolis-hastings-sampling.py └── pymc3_example.py ├── Chapter05 ├── factor_analysis.py ├── gaussian_mixture.py ├── ica.py ├── parameter_estimation.py └── pca.py ├── Chapter06 ├── SOM.py ├── covariance_rule.py ├── hebb_rule.py ├── rubner_tavan_network.py └── sanger_network.py ├── Chapter07 ├── evaluation_metrics.py ├── fuzzy_cmeans.py ├── k_nearest_neighbors.py ├── kmeans.py ├── metrics.py └── spectral_clustering.py ├── Chapter08 ├── adaboost.py ├── gradient_tree_boosting.py ├── random_forest.py └── voting_classifiers.py ├── Chapter09 ├── batch_normalization.py ├── dropout.py ├── mlp.py └── perceptron.py ├── Chapter10 ├── dcn.py ├── dcn_da.py └── recurrent.py ├── Chapter11 ├── dca.py ├── denoising_dca.py ├── sparse_dca.py └── variational_dca.py ├── Chapter12 ├── dcgan.py └── wgan.py ├── Chapter13 ├── supervised_dbn.py └── unsupervised_dbn.py ├── Chapter14 ├── policy_iteration.py ├── td0.py └── value_iteration.py ├── Chapter15 ├── actor_critic_td0.py ├── q_learning.py ├── q_learning_nn.py ├── sarsa.py └── td_lambda.py ├── LICENSE └── README.md /Chapter01/cross_validation.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Mastering-Machine-Learning-Algorithms/HEAD/Chapter01/cross_validation.py -------------------------------------------------------------------------------- /Chapter01/cross_validation_2.py: -------------------------------------------------------------------------------- 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