Overview
The course introduces the most important algorithmic and statistic machine learning tools. The first part of the course focuses on the statistical foundations and on the methodological aspects. The second part is more hands-on, with practical applications to help develop the necessary software skills.
The course aims at teaching a methodological and practical overview to statistical learning methods. The emphasis is on the applications and state-of-the-art techniques are presented through hands-on tutorial with R. The focus will be on business-oriented libraries allowing to integrate statistical models into production-ready tools.
R Programming:
Statistics & ML:
- Feature Engineering and Selection
- Tidy Modelling with R
- Stacking with R
- AutoML with H2O
- Deep Learning with Keras
Everything with R: