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
01
Foundations
The mathematics and neural-network mechanics everything else assumes.
4decks
707cards
Mathematical Foundations
Linear algebra, probability, calculus and optimisation — the machinery every model is built on.
Tensors & Neural Plumbing
Shapes, matmuls, forward and backward passes, parameter counts, memory footprints.
Deep Learning Building Blocks
Convolutions, recurrence, normalisation, activations, optimisers and regularisation.
Information Theory for Language
Entropy, cross-entropy, KL, perplexity, calibration, and language modelling as compression.