epfml/ML_course

EPFL Machine Learning Course, Fall 2026

What it solves

This repository provides a centralized hub for students to access the complete curriculum, practical exercises, and project materials for the EPFL Machine Learning course (CS-433).

How it works

The repository acts as a library for the course, hosting lecture notes, code templates, and solutions. It integrates with external platforms like the official course website for syllabus details, a media channel for lecture recordings, and a discussion forum for student support.

Who it’s for

It is primarily designed for students enrolled in the EPFL Machine Learning course who need access to instructional materials, coding assignments, and project resources.

Highlights

  • Access to comprehensive lecture notes and course materials.
  • Includes practical code templates and solutions for labs.
  • Links to archived lecture videos from current and previous years.
  • Integrated support channels via discussion forums and email.

Related

  • Project
    NVIDIA-NeMo/RL

    NeMo RL is an open-source post-training library for scalable reinforcement learning of large multimodal models (LLMs, VLMs). It provides algorithms like GRPO, DAPO, and SFT, with flexible backends for distributed training and generation.

  • Project
    gavinkhung/machine-learning-visualized

    Machine Learning Visualized is a collection of interactive Jupyter Notebooks and documentation that explains machine learning algorithms through mathematical derivations and visual training simulations.

  • Project
    Farama-Foundation/ViZDoom

    A Doom-based AI research platform for developing and testing bots that play the game using only visual information, primarily for reinforcement learning research.

  • Project
    deepcharles/ruptures

    A Python library for off-line change point detection used to analyze and segment non-stationary signals.