Table of Contents:
1 Introduction to Machine Learning
2 Preparing to Model
3 Modelling and Evaluation
4 Basics of Feature Engineering
5 Brief Overview of Probability
6 B ayesian Concept Learning
7 Super vised Learning: Classification
8 Super vised Learning: Regression
9 Unsupervised Learning
10 Basics of Neural Network
11 Other Types of Learning