Welcome to the first week of the "How to Win a Data Science Competition" course! This is a short summary of what you will learn.

• Mikhail Trofimov will introduce you to competitive data science . You will learn about competitions' mechanics, the difference between competitions and a real-life data science, overview hardware and software that people usually use in competitions. We will also briefly recap major ML models frequently used in competitions.

• Alexander Guschin will summarize approaches to work with features : preprocessing, generation and extraction . We will see, that the choice of the machine learning model impacts both preprocessing we apply to the features and our approach to generation of new ones. We will also discuss feature extraction from text with Bag Of Words and Word2vec, and feature extraction from images with Convolution Neural Networks.

Let's go ahead and get started!