what is ml-for-beginners fr?

This repository is a free, self-paced course from Microsoft Cloud Advocates that teaches Machine Learning to people who are new to it. The README describes it as a 12-week, 26-lesson curriculum about Machine Learning, focused on what it calls classic machine learning, the more established techniques that came before today's deep neural networks, using primarily the Scikit-learn library and explicitly avoiding deep learning, which is covered in a separate AI for Beginners course. The everyday problem it tries to solve is that Machine Learning is intimidating to start: there are too many scattered tutorials and not enough end-to-end practice. ML-For-Beginners walks a learner through the field in small, consistent steps. Each lesson includes a pre-lesson quiz, written instructions for the lesson itself, a worked solution, an assignment, and a post-lesson quiz. The framing is travel-themed, examples and datasets come from world cultures, and the pedagogy is project-based, meaning learners build small projects as they go rather than just reading. Some R lessons are included alongside the main Python material. You would reach for this if you are a student or self-learner who wants an organized introduction to machine learning with quizzes, exercises and reference solutions, or an instructor who wants ready-made coursework for a study group. The README asks learners to fork and clone the repo and step through the lessons in order. The lessons are delivered as Jupyter Notebooks, and the README lists automatically maintained translations into more than fifty languages.