Synopsis

In this talk, we will discuss the basics of machine learning: a supervised learning framework and neural networks. In particular, we will cover the following topics, focussing on the intuition behind them:

(1) Types of machine learning

(2) Neural networks, from perceptron, MLP to deep neural networks

(3) Training, overfitting and regularization

(4) Practical considerations for applying ML

(5) Challenges of deep learning.