- Complete ML curriculum by Microsoft
- Beginner-friendly projects
github.com/microsoft
Link audit notes: the original list circulated with shortened lnkd.in redirect links, which cannot be resolved outside a browser session. Each entry below was independently identified and verified against its live GitHub repository — all 16 are active, correctly matched to their descriptions, and linked directly to github.com.
The Reading List
16 repositories spanning ML fundamentals, deep learning, LLMs, agents, RAG, NLP, and reinforcement learning.
- Daily ML practice roadmap
- Build consistency while learning
github.com/Avik-Jain
- 200+ algorithms explained
- Great for ML fundamentals
github.com/TheAlgorithms
- Linear algebra & calculus foundations
- Essential ML math concepts
github.com/dair-ai
- Learn ML with real-world workflows
- Covers data, modeling, deployment
github.com/GokuMohandas
- 60+ DL research papers reproduced
- Learn by rebuilding models
github.com/labmlai
- Build neural networks from scratch
- Learn how models actually work
github.com/karpathy
- Practical guide to LLMs
- Training and applications
github.com/HandsOnLLM
- Prompt techniques and frameworks
- Real examples included
github.com/dair-ai
- Build agent-based systems
- Concepts + practical code
github.com/microsoft
- Patterns for building AI agents
- Autonomous workflows
github.com/NirDiamant
- 25+ retrieval-augmented generation methods
- Practical implementations
github.com/NirDiamant
- Practical datasets and applications
- Learn by solving real problems
github.com/academic
- Massive NLP resource list
- Tools, papers, and datasets
github.com/keon
- Curated RL research resources
- Tutorials and libraries
github.com/aikorea
- Understand RL step-by-step
- Build algorithms yourself
github.com/KhashayarRahimi