Machine learning using MATLAB

This one-semester course provides a first introduction to machine learning including the following topics:

  • Linear regression
  • Logistic regression
  • Support vector machines
  • Deep Neural network
  • Dimensionality reduction
  • Clustering
  • Anomaly detection

complemented by a exercise session of practical Matlab exercises. 

Note:

  • Online lecture room is here

Prerequisites

None, if taken as a master course. If taken as an advanced course in the bachelor program:

  • basic math courses offered in our bachelor programs
  • algorithms and data structures
  • introduction to computer science including programming

Learning objective

You will

  • have an insight of the fundamentals of Machine Learning
  • have the ability to design your own machine learning algorithm to solve some specific problems with Matlab
  • know how to improve the performance using training data

Reference 

Textbook

  • Christopher M.. Bishop. Pattern recognition and machine learning. Springer, 2006.
  • Alpaydin, Ethem. Introduction to machine learning. MIT press, 2014.
  • Ian Goodfellow, Yoshua Bengio, Aaron Courville. Deep learning. MIT press, 2016