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.