Machine Learning: An Introduction

Topics

• Common machine
• Intended topics are
• Linear methods for regression and classification
• Nearest neighbours
• Decision trees
• Bias-variance trade-off
• Neural networks
• Deep neural nets
• Convolutional nets
• Generative adversarial nets and variational autoencoders
• Clustering
• Principal component analysis
• Gaussian mixture models and the EM algorithm
• Basics of reinforcement learning