• Lecturer: Ivan P. Yamshchikov
• Date: Friday, 12.00-13.30
• Room: A3 02
• Language: English
• First class: April 16
• Target audience: MSc students, PhD students, Postdocs
• Prerequisites: Basic knowledge about real world, Analysis, general understanding of Probability and Statistics

Abstract:

There is a fundamental difference of approach between deductive (model-based) and inductive (data-based) reasoning in sciences. In this crush course we will focus on latter approach that is rarely used in pure mathematics yet might be useful in the applied research. We cover the following models and topics:

• General principles of data-driven approach: bottle-necks and advantages;
• Regression, Classification;
• Principle Component Analysis, clustering;
• Decision trees, random forests, gradient boosting;
• Neural networks, general principles and basic models

As we cover the most general and widely used models we will come back to the first topic revisiting it of a different level.