Orateurs
Claudia Beleites
Martino Sorbaro
Description
In this class, we will give an introduction to machine learning algorithms, in a data-oriented and coding-oriented way. We will explain what it means for an algorithm to learn, and the main categories of ML problems. We will then cover, with code examples, how to approach a dataset for analysis. In particular we will take a closer look at: automated clustering of data points; supervised classification; supervised regression; how to test a model and choose hyperparameters; dimensionality reduction. The workshop will be as hands-on as possible. A basic knowledge of Python is required.
