Fundamental and Hands-on Introduction to Machine Learning


This talk aims at providing key concepts of Machine Learning through real examples. Linear models in regression and classification are introduced along with some tasks. Some gradient-based optimization and penalization techniques are also discussed from Linear Regression to Deep Neural Networks. The slide can be found here: Introduction to Machine Learning. For those who want to play with the codes, you can find jupyter notebook of the simulation here: Teaching repository.