A real Caltech course, not a watered-down version.
This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications.
ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML has become one of the hottest fields of study today, taken up by graduate and undergraduate students from 15 different majors at Caltech.
This course balances theory and practice, and covers the mathematical as well as the heuristic aspects.
Summary of Course Features
- An introductory Machine Learning online course (MOOC);
- Requirements: Basic probability, matrices, and calculus;
- Instructor: Professor Yaser Abu-Mostafa;
- Lectures recorded from a live broadcast, including Q&A;
- 8 homework sets and a final exam;
- Discussion forum for participants;
- Topic-by-topic video library for easy review.