This real Caltech Introductory Machine Learning course will be broadcast live, and will be freely available. Prerequisites: Basic probability, matrices, and calculus. Live Q&A and online homeworks
Learning from Data
A real Caltech course, not a watered-down version
Broadcast live from the lecture hall at Caltech, April - May 2012.
REGISTRATION OPENS THE WEEK OF MARCH 26
- Introductory Machine Learning course
- Free, live broadcast online
- Taught by Caltech Prof. Yaser Abu-Mostafa [article]
- Prerequisites: Basic probability, matrices, and calculus
- Live Q&A and online homeworks
- Scoreboard ranking of participants
open to all participants
This is an introductory course on machine learning that covers the basic theory, algorithms, and applications. Machine learning (ML) enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML techniques are widely applied in engineering, science, finance, and commerce to build systems for which we do not have full mathematical specification (and that covers a lot of systems). The course balances theory and practice, and covers the mathematical as well as the heuristic aspects.
For more information, see