This repository serves as a curated, community-driven list of technical resources for AI developers, focusing on courses, books, and tutorials in artificial intelligence, deep learning, and machine learning. It aims to provide a centralized, easily updatable reference for experienced software engineers and coders looking to deepen their knowledge in these fields, with a strong emphasis on free and accessible materials.

How It Works

The project is a static collection of links and descriptions, maintained as a public GitHub repository. Resources are categorized by topic (AI Courses, Books, Math, Computer Science/Python, Older Materials) and difficulty level (Introductory, Intermediate, Advanced). The maintainer encourages community contributions via pull requests or email, fostering a collaborative approach to resource curation.

Quick Start & Requirements

This is a resource list, not executable code. No installation or specific software requirements are needed beyond a web browser to access the linked materials.

Highlighted Details

• Extensive categorization of resources, including specific sub-fields like Reinforcement Learning, NLP, and Computer Vision.
• Clear distinction between free and paid resources, with notes on auditing options for paid courses.
• Includes foundational math and computer science prerequisites essential for AI/ML development.
• Features direct links to official documentation and tutorials from major AI frameworks like TensorFlow and PyTorch.

Maintenance & Community

The project is maintained by Duncan, a co-founder of Rose City Robotics, and actively welcomes community contributions. Rose City Robotics is a robotics integrator focused on AI for EV battery recycling.

Licensing & Compatibility

The repository itself is likely under a permissive license (e.g., MIT, Apache 2.0) given its nature as a resource list, but specific licensing for the linked external resources varies. Compatibility is high for any user with internet access.

Limitations & Caveats

As a curated list, the quality and relevance of external resources are subject to change and depend on the original providers. The "paid" designation is based on the maintainer's last update and may not reflect current pricing or access models.