Flashcards

11,105 cards in 101 decks, written from the same source as the concepts. Space to flip, arrows to move, K and R to sort what you know from what you do not. Progress lives in your browser.

All decks 01Foundations 02Transformer Internals 03Training & Fine-Tuning 04Reinforcement Learning 05Inference, Systems & Hardware 06Applied LLM Engineering 07Reasoning, Evaluation & Safety 08Multimodal & Applications 09Classical ML & Statistical Learning 10Causal Inference & Experimentation 11Time Series & Forecasting 12Graphs, Recommenders & Structured Data 13Generative Modelling Beyond Transformers 14Efficiency, Compression & Edge AI 15Search & Information Retrieval 16Data & Feature Engineering 17MLOps & Platform Engineering 18Security, Privacy & Adversarial ML 19Governance, Risk & Responsible AI 20Human-AI Interaction, Product & Economics

Reinforcement Learning

Classical RL, then the specific dialect of it that post-trains language models.

5decks

489cards

RL Foundations

MDPs, value functions, TD learning, policy gradients, actor-critic, TRPO and PPO.

140 cards 20 concepts

RL for Language Models

RLHF as an RL problem, KL-regularised objectives, GRPO, RLVR, and reward over-optimisation.

142 cards 21 concepts

Bandits & Exploration

Regret, UCB, Thompson sampling, contextual bandits, and exploration under a budget.

68 cards 7 concepts

Offline & Model-Based RL

Learning from logged data, distribution shift, conservative value estimation, world models and planning.

72 cards 7 concepts

Multi-Agent RL

Self-play, equilibria, credit assignment across agents, emergent coordination and non-stationarity.

67 cards 6 concepts