EPFL Fundamentals in Statistical Pattern Recognition

Welcome to the webpage of the EPFL course EE-612 “Fundamentals in Statistical Pattern Recognition” (FSPR).

This was a course on fundamentals of Machine Learning from the Doctoral Program at Ecole Polytechnique Fédérale de Lausanne (EPFL) taught from 2013 to 2023 on the spring semester every 2 years.

This course was designed to serve as a pre-requisite for more advanced courses on Machine Learning already taught at EPFL. This course presents the functioning details of fundamental supervised and unsupervised models, ranging from regression and classification to probability distribution modeling. The learning outcome for students is to get an in-depth understanding of the most fundamental algorithms in statistical pattern recognition (aka machine learning) as well as concrete tools (as Python source code). Labs play a central role (hands-on) in the course with guided programming labs in Python for a deep understanding of algorithms.

The course became popular across various sections at EPFL as it provided basics in machine learning and deep learning. The practical approach to the topic and the hands-on labs were greatly appreciated.