ChristosChristofidis/awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
You can also find the most cited deep learning papers from here Have anything in mind that you think is awesome and would fit in this list? Feel free to send a pull…
Read the full README ↗ · Preview checked 2026-10-26T23:12:17.868Z
Inside the original README — Document outline
- Awesome Deep Learning [](https://github.com/sindresorhus/awesome)
- Table of Contents
- Books
- Courses
- Videos and Lectures
- Papers
- Tutorials
- Researchers
- Websites
- Datasets
- Conferences
- Frameworks
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Links from the README
References supplied by the publisher, not independently verified endorsements. Check the destination before downloading files or entering credentials.
- Papers
- Tutorials
- Datasets
- AWS Machine Learning
- Medical Imaging with Deep Learning Tutorial
- Multi-task CNN: a real-world example by Andrew Ferlitsch
- Training a Reinforcement Learning Agent by Miguel Morales
- here
- Siamese Neural Networks for One-shot Image Recognition
- Torch7 Tutorials
- The Best Machine Learning Tutorials On The Web
- TensorFlow tutorials
Documentation belongs to its respective authors. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
What this repository does
A curated list of awesome Deep Learning tutorials, projects and communities.
Repository facts
- Owner
- ChristosChristofidis
- Primary language
- Not reported
- Stars
- 29,114
- Forks
- 6,345
- Open issues + pull requests
- 92
- License
- Not reported — inspect the license file
- Archived
- No
- Default branch
- master
- Created
- 2015-01-02T19:28:35.000Z
- Last push
- 2025-05-26T12:28:00.000Z
Topics and intended use
Owner-supplied topics: awesome, awesome-list, deep-learning, deep-learning-tutorial, deep-networks, face-images, machine-learning, neural-network, recurrent-networks
Review the README for scope, installation, examples and limitations. We do not run repository code or certify it.
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Source and freshness
Source: GitHub. Metadata observed 2026-10-31T12:19:22.904Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.