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Learning PRML

This is a repo for test implementation while learning PRML. Take anything you want. Use at your own risk.

Current implementations includes:

  • Linear

    • Linear Regression
    • Logistic Regression

  • Neural Network

    • Back Propagation Network
    • Back Propagation Perceptron
    • Simple CNN (on TensorFlow)

  • Probabilistic

    • Gaussian Mixture Model
    • EM (expectation maximization) algorithm on GMM
    • Gibbs sampling methods on GMM

  • kNN Classifier

  • Naive Bayes Classifer

  • Notes on lots of subjects

Comments and discussion are welcomed!

For formula not rendered porperly in Github preview, you may use chrome + 'GitHub with MathJax'. Or you may clone the code and use sublime + OmnipotentMarkup or any other mathjax support you prefer to view the markdown notes.