ml-retreat

A personal repository of learning notes for advanced AI studies

CommonProductEducationArtificial IntelligenceMachine Learning

ml-retreat is a personal repository for advanced learning in artificial intelligence. It provides an in-depth understanding of the fundamentals of machine learning as well as essential reading/viewing resources on more nuanced topics. The goal of this project is to study the 30 essential research papers recommended by Ilya Sutskever, the Distilled AI blog, various AI/ML video playlists, and to gain deep insights into and implementations of Transformers, LLMs, and related themes.

Provide an in-depth understanding of advanced topics in machine learning
Include links to essential research papers and resources
Record the author's personal learning notes and insights
Cover core AI technologies such as LLMs and Transformers
Offer learning paths for advanced topics like quantum machine learning
Jax
Energy-Based Models
etc.
Support tracking and updates through GitHub

\The target audience includes researchers
developers
and students in the field of machine learning. This project is suitable for them as it offers a structured learning path that encompasses both basic and advanced machine learning knowledge
along with a wealth of learning resources that help systematically enhance their professional skills in AI.\

Researchers can stay updated on the latest AI research advancements by reading the 30 essential research papers recommended by Ilya Sutskever.
Developers can utilize the resources in this project to deepen their understanding of the Transformers model and apply it to real-world projects.
Students can follow the learning paths offered in this project to systematically study machine learning as a supplement to their coursework.

1. Visit the ml-retreat project page on GitHub.
2. Browse the project's README file to understand its goals and structure.
3. Select a learning path of interest based on individual learning needs
such as LLMs
Transformers

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