ML-Course-Notes VS Awesome-pytorch-list

Compare ML-Course-Notes vs Awesome-pytorch-list and see what are their differences.

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ML-Course-Notes Awesome-pytorch-list
117 2
5,819 14,952
0.0% -
0.0 0.0
about 1 year ago 3 months ago
GNU General Public License v3.0 or later -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

ML-Course-Notes

Posts with mentions or reviews of ML-Course-Notes. We have used some of these posts to build our list of alternatives and similar projects.

Awesome-pytorch-list

Posts with mentions or reviews of Awesome-pytorch-list. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-19.

What are some alternatives?

When comparing ML-Course-Notes and Awesome-pytorch-list you can also consider the following projects:

ML-YouTube-Courses - 📺 Discover the latest machine learning / AI courses on YouTube.

awesome-asyncio - A curated list of awesome Python asyncio frameworks, libraries, software and resources

RubixML - A high-level machine learning and deep learning library for the PHP language.

awesome-codex - A list dedicated to products, demos and articles related to 🤖 OpenAI's Codex.

Transformers-Recipe - 🧠 A study guide to learn about Transformers

500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code - 500 AI Machine learning Deep learning Computer vision NLP Projects with code

awesome-document-understanding - A curated list of resources for Document Understanding (DU) topic

3D-Machine-Learning - A resource repository for 3D machine learning

awesome-deep-learning - A curated list of awesome Deep Learning tutorials, projects and communities.

build-your-own-x - Master programming by recreating your favorite technologies from scratch.

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.