Notes on Pattern Recognition and Machine Learning

This repository contains a collection of ipython notebooks with notes, experiments and simulations for different chapters of the "Pattern Recognition and Machine Learning" book.

Introduction (Chapter 1)

1. Preliminaries

2. Maximum Likelihood Estimation (MLE)

Linear Models for Regression (Chapter 3)

Appendix

1. Biased and Unbiased Point Estimators - Mean and Variance (simulations)