Statistical-Machine-Learning---Model-Algorithm-and-Application

The implementations of classical machine learning algorithms

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
Datasets		Datasets
Boosting.ipynb		Boosting.ipynb
Convolutional Neural Networks --- Conv & Pool Layer.ipynb		Convolutional Neural Networks --- Conv & Pool Layer.ipynb
Decision Tree.ipynb		Decision Tree.ipynb
Fused Lasso.ipynb		Fused Lasso.ipynb
Gaussian Bayes.ipynb		Gaussian Bayes.ipynb
Gaussian Mixture Model.ipynb		Gaussian Mixture Model.ipynb
Group lasso via proximal gradient descent.ipynb		Group lasso via proximal gradient descent.ipynb
Hidden Markov Models.ipynb		Hidden Markov Models.ipynb
K-Means Algorithm.ipynb		K-Means Algorithm.ipynb
K-Nearest Neighbors Algorithm.ipynb		K-Nearest Neighbors Algorithm.ipynb
LICENSE		LICENSE
Learning Theory.ipynb		Learning Theory.ipynb
Linear Models.ipynb		Linear Models.ipynb
Logistic Regression.ipynb		Logistic Regression.ipynb
Markov Process.ipynb		Markov Process.ipynb
Naive Bayes.ipynb		Naive Bayes.ipynb
Neural Networks.ipynb		Neural Networks.ipynb
Parametric Regression.ipynb		Parametric Regression.ipynb
Perceptron.ipynb		Perceptron.ipynb
Probabilistic Graphical Models.ipynb		Probabilistic Graphical Models.ipynb
Python Numerical Methods.ipynb		Python Numerical Methods.ipynb
README.md		README.md
Sampling Methods.ipynb		Sampling Methods.ipynb
Support Vector Machine.ipynb		Support Vector Machine.ipynb
Text Mining.ipynb		Text Mining.ipynb

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