Machine Learning

Machine learning is a class of methods of artificial intelligence, the characteristic feature of which is not a direct solution of the problem, but learning by solving many similar problems. For construction of such methods means of mathematical statistics, numerical methods, methods of optimization, the theory of probability, the theory of graphs are used. Many methods of machine learning were developed as an alternative to classical statistical approaches.

Useful literature

1. Kulkarni, Sanjeev, and Gilbert Harman. An Elementary Introduction to Statistical Learning Theory, John Wiley & Sons, Incorporated, 2011 (access via the HSE Library).
2. Harman, Gilbert, and Sanjeev Kulkarni. Reliable Reasoning: Induction and Statistical Learning Theory, edited by Tom Roeper, MIT Press, 2007 (access via the HSE Library).
3. Alpaydin, Ethem. Introduction to Machine Learning, MIT Press, 2014 (access via the HSE Library).
4. Mohri, Mehryar, et al. Foundations of Machine Learning, MIT Press, 2012 (access via the HSE Library).
5. Murphy, Kevin P.. Machine Learning : A Probabilistic Perspective, MIT Press, 2012 (access via the HSE Library).