A guide to building long-term compounding knowledge infrastructure. See details on GitHub .

EPFL Machine Learning Course CS-433

EPFL Machine Learning Course CS-433 offers comprehensive coverage of theory and practice, including lectures, labs, projects, and video resources.

Introduction

EPFL Machine Learning Course CS-433 is designed for undergraduate and graduate students, covering core theory, algorithms, applications, and ethics, with extensive lectures, labs, and project resources.

Key Features

  • Systematic coverage of machine learning fundamentals
  • Includes lectures, labs, projects, and code templates
  • Weekly video lectures and Q&A
  • Public access to past exams and solutions
  • Open-source resources for self-study and review

Use Cases

  • University machine learning course instruction
  • Self-study and advanced learning
  • Project practice and team collaboration
  • Reviewing and supplementing course content

Technical Highlights

Course resources are mainly in Jupyter Notebook and Python, accessible across platforms, continuously updated, and open for community contributions.

Comments

EPFL Machine Learning Course CS-433
Resource Info
Author EPFL
Added Date 2025-09-11
Tags
OSS Data Course