Awesome AI
by owainlewis · owainlewis/awesome-artificial-intelligence
A curated list of Artificial Intelligence courses, books and lectures.
The canonical AI theory text (Russell, Norvig).
Transformers in raw PyTorch, layer by layer (Sebastian Raschka).
Mathematical foundations of neural networks (Goodfellow, Bengio, Courville).
Bishop's 2024 update; probability-grounded modern DL (Bishop & Bishop).
Visual + practical guide to LLM applications (Jay Alammar, Maarten Grootendorst).
Production LLMOps: fine-tuning, quantization, serving (Labonne, Iusztin).
RL foundations (Sutton, Barto).
The NLP reference, kept current through the deep learning era (Jurafsky, Martin).
Concise, math-grounded path from n-grams to transformers (Andriy Burkov).
Anthropic's CLI agent; multi-file codebase refactoring with long context.
GGoogle's official open-source terminal agent; long-context repo exploration.
Google's Agent Development Kit (Python, Java). Great local development experience + A2A + MCP.
Data framework for ingesting, indexing, and querying private data with LLMs.
Extremely minimalist AI agent framework in just 100 lines of code. Fantastic way to learn.
Typed, structured LLM orchestration framework built on Pydantic models for safe, predictable outputs.
— ⭐ Patterns, pitfalls, and tradeoffs for designing AI agents.
Example code, recipes, and best practices for working with OpenAI APIs.
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