AI/ML Master Foundations — Curated Research Book Collection

Summary

I put this collection together after spending a lot of time reading what I think are some of the best books on AI, machine learning, deep learning, probabilistic modeling, optimization, reinforcement learning, transformers, LLMs, validation, and fairness. I want to share this with the community for one simple reason: I want to give people a structured path through the books that actually help them understand things deeply, instead of sending them through random courses, disconnected tutorials, and fragmented content.

Keywords

hf-dataset language-modeling · -qa · -summarization · -embeddings---similarity · -embeddings · -nlp---zero-shot · -nlp---ner · -reinforcement-learning document datasets mlcroissant agent ai artificial-intelligence machine-learning ml deep-learning dl neural-networks representation-learning supervised-learning unsupervised-learning semi-supervised-learning self-supervised-learning probabilistic-ml bayesian-learning statistical-learning ml-theory learning-theory generalization optimization convex-optimization gradient-descent stochastic-gradient-descent information-theory entropy kl-divergence causal-inference causality decision-making reinforcement-learning rl multi-agent bandits markov-decision-process transformers attention large-language-models llm foundation-models generative-ai generative-models diffusion-models vae gan autoregressive-models language-modeling nlp natural-language-processing computer-vision multimodal embeddings feature-extraction transfer-learning fine-tuning prompt-engineering rag retrieval-augmented-generation ai-agents ai-engineering ml-engineering model-training model-evaluation validation robustness safety trustworthy-ai explainability interpretability fairness bias responsible-ai dataset benchmark research education textbooks books learning-resources study-guide curriculum knowledge-base open-science pytorch tensorflow huggingface transformers-library

Topics

Language Modeling, QA, Summarization, Embeddings / Similarity, Embeddings, NLP / Zero-shot, NLP / NER, Reinforcement Learning

Research notes

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