Various tutorials given for welcoming new students at MILA.
The main features of mila-udem/welcome_tutorials are: Tutorials.
Open-source alternatives to mila-udem/welcome_tutorials include: d2l-ai/d2l-en — This project is an educational platform and research toolkit designed to teach deep learning through a combination of… davidbau/how-to-read-pytorch — Quick, visual, principled introduction to pytorch code through five colab notebooks. domib97/revive.nokia.n95 — Revive your old S60 3rd FP1 Nokia N95 2GB with this guide from 2021 ! dsksd/deepnlp-models-pytorch — Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ). hunkim/pytorchzerotoall — PyTorchZeroToAll is an educational resource and collection of tutorials focused on deep learning and the PyTorch… atcold/pytorch-deep-learning-minicourse — This is an educational curriculum for building and training neural networks using PyTorch. It serves as a deep…
This project is an educational platform and research toolkit designed to teach deep learning through a combination of mathematical theory, visual diagrams, and executable code. It provides a comprehensive environment for building, training, and evaluating neural networks, grounding complex concepts in interactive computational notebooks that allow for hands-on experimentation. The framework distinguishes itself by interleaving theoretical foundations—including linear algebra, calculus, and probability—with practical implementations across multiple industry-standard libraries. It supports flex
Quick, visual, principled introduction to pytorch code through five colab notebooks.
Revive your old S60 3rd FP1 Nokia N95 2GB with this guide from 2021 !
This is an educational curriculum for building and training neural networks using PyTorch. It serves as a deep learning training guide and resource, providing a structured series of lessons on tensor computation and architecture development. The course uses an interactive learning model that synchronizes academic theory with practice. It pairs theoretical lecture slides with exercise-driven notebooks, requiring students to implement model logic within predefined templates to validate their conceptual understanding. The curriculum covers a broad range of deep learning capabilities, including