what is nyu-dlsp20 fr?

This repository contains the course materials for NYU's Deep Learning course from Spring 2020, taught by Alfredo Canziani. The course covers how to build and train neural networks, the branch of artificial intelligence that powers most modern AI applications. All lecture videos and written notes are available on the companion website at atcold.github.io/NYU-DLSP20. The repository itself holds interactive coding exercises in the form of Jupyter Notebooks, which are documents that mix written explanations with runnable code. Each notebook corresponds to a lecture topic, and students can follow along by running the code on their own machine and experimenting with it directly. The exercises use PyTorch, a popular Python library for building neural networks. To run the notebooks locally, you need to install Miniconda (a lightweight Python environment manager), clone this repository, create the provided conda environment, and then launch Jupyter from the terminal. Detailed setup instructions for Mac, Linux, and Windows are included in the README. The course materials have been translated into at least fourteen languages by community contributors, including Mandarin, Spanish, French, Japanese, Arabic, Russian, and Portuguese, among others. Each translation lives in its own folder within the repository. This is a standalone educational resource, not an active software project. It exists as an archive of a university course that anyone can work through at their own pace.