ml

A didactic Python "library" with well-commented and annotated implementations of machine learning algorithms.

Name		Name	Last commit message	Last commit date
_datasets		_datasets
_normalization		_normalization
.gitignore		.gitignore
README.md		README.md
_linalg.py		_linalg.py
_normalizers.py		_normalizers.py
canonical_correlation_analysis.py		canonical_correlation_analysis.py
factor_analysis.py		factor_analysis.py
gaussian_mixture_model.py		gaussian_mixture_model.py
gaussian_process_regressor.py		gaussian_process_regressor.py
ibfa.py		ibfa.py
k_means.py		k_means.py
neural_network.py		neural_network.py
probabilistic_canonical_correlation_analysis.py		probabilistic_canonical_correlation_analysis.py
probabilistic_principal_component_analysis.py		probabilistic_principal_component_analysis.py
randomized_singular_value_decomposition.py		randomized_singular_value_decomposition.py
reparameterization_trick.py		reparameterization_trick.py

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