Descriptif

Machine learning is an increasingly important topic in science and industry, and is involved in many of the recent advances of artificial intelligence (AI). This course covers the main concepts, paradigms and algorithms in machine learning. Emphasis is put both on building solid theoretical foundations as well as being able to master a complete pipeline from problem formulation and data pre-processing to model testing and evaluation, thus preparing students for developing and deploying real-world machine-learning solutions. We will work with Python 3 and scientific libraries such as Numpy, Scikit-Learn, and PyTorch.