Machine Learning studies representations and algorithms that allow machines to improve their performance on a task from experience. This is a broad overview of existing methods for machine learning and an introduction to adaptive systems in general. Emphasis is given to practical aspects of machine learning and data mining.
Why did I take this class??
I thought it would be decently interesting.
Summary
This class did not really meet my expectations from before taking the course, but in retrospect it was about what you might expect for an undergraduate machine learning course.
A lot of different topics are covered, and it feels like a survey of various machine learning algorithms.
The projects were trivial nearly one-line additions to existing code, which felt too easy. The homeworks were Canvas quizzes which I really did not like.
The midterm and take-home final exam were pretty easy, and grading was extremely generous.
After taking this class, I feel less inclined to take the course on AI (CMSC421).