Taught by Feynman Prize winner Professor Yaser Abu-Mostafa.
The fundamental concepts and techniques are explained in detail. The focus of the lectures is real understanding, not just "knowing."
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 undergraduate and graduate students from 15 different majors at Caltech. This course balances theory and practice and covers the mathematical as well as the heuristic aspects. The lectures below follow each other in a story-like fashion:
What is learning?
Can a machine learn?
How to do it?
How to do it well?
Take-home lessons.
This course is taught be Caltech additional recourses on the course can be found at: [ Ссылка ]
Machine Learning Tutorial Caltech Lecture 7 - The VC Dimension
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