Annotated Deep Learning Paper Implementations
Focus: papers, transformers and tutorials. Shares deep learning and pytorch with Dive into Deep Learning. Rated 4.8 (Dive into Deep Learning: 4.9).
Course
Interactive deep learning book with code, math and discussions.
Rating
4.9 / 5
Pricing
Free
Difficulty
Intermediate
Works on
Web
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Dive into Deep Learning (d2l) is a free interactive book with multi-framework code (PyTorch, JAX, TensorFlow, MXNet), math and discussions — adopted at 500 universities across 70 countries including Stanford, MIT, Harvard and Cambridge.
Third-party open-source projects. We are not affiliated with their authors; repositories are provided as-is by their maintainers. Review each project's license, code and security before installing. See our Disclaimer.
Students and engineers who want a rigorous, hands-on deep learning education.
People looking for a quick, casual intro.
See how Dive into Deep Learning stacks up, side by side, plus the lists it made.
Not sold on Dive into Deep Learning? These do a similar job, and each card says what it has in common.
Focus: papers, transformers and tutorials. Shares deep learning and pytorch with Dive into Deep Learning. Rated 4.8 (Dive into Deep Learning: 4.9).
Focus: machine learning and python. Shares deep learning and course with Dive into Deep Learning. Rated 4.8 (Dive into Deep Learning: 4.9).
Focus: llm, roadmap and colab. Shares course and free with Dive into Deep Learning. Rated 4.8 (Dive into Deep Learning: 4.9).
Focus: machine learning, mlops and production ml. Shares course and free with Dive into Deep Learning. Rated 4.8 (Dive into Deep Learning: 4.9).
Focus: reinforcement learning, openai and deep rl. Shares course and open source with Dive into Deep Learning. Rated 4.7 (Dive into Deep Learning: 4.9).
Focus: ai agents, microsoft and lessons. Shares course and free with Dive into Deep Learning. Rated 4.8 (Dive into Deep Learning: 4.9).
Want to spend nothing? These free picks cover similar ground.
Focus: gpt, llm and training. Shares pytorch and open source with Dive into Deep Learning. A framework, not a course. Adds macOS, Windows and Linux. Rated 4.8 (Dive into Deep Learning: 4.9).
Focus: math, machine learning and linear algebra. Shares book and free with Dive into Deep Learning. Rated 4.7 (Dive into Deep Learning: 4.9).
Focus: pdf, mit and goodfellow. Shares deep learning and book with Dive into Deep Learning. Rated 4.7 (Dive into Deep Learning: 4.9).
Focus: ai agents, scientific research and skills. Shares open source and free with Dive into Deep Learning. An AI tool, not a course. Rated 4.7 (Dive into Deep Learning: 4.9).
Focus: lectures, machine learning and reinforcement learning. Shares deep learning and free with Dive into Deep Learning. Rated 4.5 (Dive into Deep Learning: 4.9).
Focus: llm, tutorial and from scratch. Shares deep learning and pytorch with Dive into Deep Learning. Rated 4.5 (Dive into Deep Learning: 4.9).
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