18-661: 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.
In Fall 2019 this course is broadcast between the Silicon Valley and Pittsburgh campuses, with an instructor in both locations. ECE Silicon Valley and ECE Pittsburgh students attend classes synchronously.
Last Modified: 2020-12-01 12:06PM
- Spring 2021
- Fall 2020
- Spring 2020
- Fall 2019
- Spring 2019
- Fall 2018