18-461: Introduction to Machine Learning for Engineers
This course provides an introduction to machine learning with a special focus on engineering applications. The course starts with a mathematical background required for machine learning and covers approaches for supervised learning (linear models, kernel methods, decision trees, neural networks) and unsupervised learning (clustering, dimensionality reduction), as well as theoretical foundations of machine learning (learning theory, optimization). Evaluation will consist of mathematical problem sets and programming projects targeting real-world engineering applications.
This course is cross-listed with 18-661.
Anti-requisites: 10-401, 10-601, 10-701
Last Modified: 2018-11-02 3:58PM
This course is currently being offered.
- Spring 2019
- Fall 2018