Monday to Friday
This module starts with an introduction to machine learning: how it is organized, what are the sub branches of machine learning, fundamental differences between these approaches and types of problems they are designed to solve.
Next, students get familiar with framing a machine learning problem, picking up appropriate objective function and algorithm according to a given problem. It is well known that data wrangling and feature engineering takes most of the time of model development. Students learn techniques to effectively deal with missing values, outliers, categorical variables and design new features.
This course also covers algorithms that are used when the target variable which has to be predicted is known. It starts with simple KNN and ends with fully connected feed-forward neural networks. Proper testing of a model is essential to build a reliable product. Students are introduced to various testing methods and parameters that help to build generalizable and stable models.
Fee: 15000 UAH
© 2020 DevRepublik. Все Права Защищены Политика Конфиденциальности. Договор Публичной Оферты
Зареєструйся на будь-який курс до 24 квітня і отримай знижку 20%!
Зарегистрируйся на любой курс до 24 апреля и получи скидку 20%!
Register for any course until April 24 and get a 20% discount!