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.
Recommended Books:
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.
Price: Free
Visit the course page
Similar Posts You May Like:
Machine Learning (Stanford) 
Master Data Science with These Four Free Courses 
Hands-On Python and R In Data Science 
Scraping and Data Mining for Beginners and Pros 
Become a Data Scientist with Python 
Visual Navigation for Flying Robots – A Free Course 
Learn How To Put Your Machine Learning Models Into Production 
Keep Learning With These Free Alison Courses 
Learn C Programming With This Free Introductory Course 
Awesome Big Data Algorithms – A Free Course