Course Information

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.

Prerequisites: 18-202 and 15-122 and 36-217 and 21-127 Antirequisites: 10-401, 10-601, 10-701
Anti-requisites: 10-401, 10-601, 10-701

Last Modified: 2018-04-25 4:54PM

Semesters offered:

  • Fall 2018