d2l-ai / d2l-enLinks
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
☆27,223Updated last year
Alternatives and similar repositories for d2l-en
Users that are interested in d2l-en are comparing it to the libraries listed below
Sorting:
- The fastai book, published as Jupyter Notebooks☆24,003Updated last year
- A collection of various deep learning architectures, models, and tips☆17,285Updated last year
- NYU Deep Learning Spring 2020☆6,773Updated 4 months ago
- VIP cheatsheets for Stanford's CS 229 Machine Learning☆18,687Updated 5 years ago
- this repository accompanies the book "Grokking Deep Learning"☆7,647Updated last year
- The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.☆12,163Updated last month
- Python code for "Probabilistic Machine learning" book by Kevin Murphy☆6,938Updated last month
- This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.☆4,331Updated last year
- The fastai deep learning library☆27,553Updated last week
- "Probabilistic Machine Learning" - a book series by Kevin Murphy☆5,390Updated 6 months ago
- 🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, fee…☆63,919Updated last month
- Jupyter notebooks for the code samples of the book "Deep Learning with Python"☆19,659Updated last month
- Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.☆5,100Updated last year
- Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)☆9,253Updated 2 months ago
- A guideline for building practical production-level deep learning systems to be deployed in real world applications.☆4,527Updated 4 months ago
- A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dm…☆9,608Updated 2 years ago
- Visualizer for neural network, deep learning and machine learning models☆31,672Updated this week
- Google Research☆36,605Updated last week
- Learn how to design, develop, deploy and iterate on production-grade ML applications.☆43,867Updated last year
- State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enter…☆14,542Updated last year
- VIP cheatsheets for Stanford's CS 230 Deep Learning☆6,811Updated 5 years ago
- Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lect…☆12,713Updated last year
- PRML algorithms implemented in Python☆11,669Updated 6 months ago
- PyTorch Tutorial for Deep Learning Researchers☆31,871Updated 2 years ago
- A playbook for systematically maximizing the performance of deep learning models.☆29,330Updated last year
- The most cited deep learning papers☆26,020Updated last year
- Latex code for making neural networks diagrams☆24,034Updated 2 years ago
- A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training☆22,853Updated last year
- Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.☆30,349Updated this week
- NYU Deep Learning Spring 2021☆1,643Updated last month