This repository contains my works on Machine Learning(Coursera) and UFLDL by Stanford.

UFLDL, Unsupervised Feature Learning and Deep Learning, changes my experience in Machine Learning tremendously. The auto-encoder algorithm, and its solid mathematical analysis and deduction are definitely important to everyone who is interested in this area.

In this part, I would commit all exercises I've done in learning UFLDL. Also I would upload all materials I've read, including the materials on the web and my notes.

                                                                                            2014-01

Here contains the lectures and notes while I learning MOOCs in Coursera, Machine Learning by Andrew Ng, and my honor code as programming exercises.

In this course, you would get a intuition about some basic algorithms. Such as regression (linear & logistic), Neural Networks, SVM (support vector machine), and Clustering (K-means),etc. Moreover, you would also learn how to evaluate a machine learning system, or how well it perform.

MATLAB is what we use in this course. I strongly recommend you to go over the video lectures of the course, and complete the revirw questions and programming exercies assigned every week.

The PDF file is a step-by-step instruction which helps you to complete the assignment and it's also a reading materials for you. Just run my main m-file, it would be okay.

                                                                                            2013-08