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657 tutors in 31 topics, built by 75 teachers. Each one follows a lesson plan its teacher wrote.

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Synthetic data for training, used with care

Synthetic data for training, used with care

Generate training data with models where it helps, and filter, verify and document it properlyAll levelsFine tuning and trainingNew
Neha Varadan$7
Causal Inference Basics

Causal Inference Basics

Estimate causal effects from observational data and state your assumptions out loudAdvancedData science and statisticsNew
Kojo Amankwah$12
Vision transformers in depth

Vision transformers in depth

Understand patch tokens, position embeddings, data needs and compute trade offs in vision transformersAdvancedComputer visionNew
Noor Siddiqui$12
NLP for multilingual and low resource languages

NLP for multilingual and low resource languages

Build and evaluate language technology for languages that most datasets and models leave behindAll levelsNLPNew
Nadia Haddad$7
Catastrophic forgetting and how to limit it

Catastrophic forgetting and how to limit it

Measure what a model loses when you fine tune it, and use replay, regularisation and merging to limit itAdvancedDeep learningNew
Neha Varadan$12
Knowledge distillation: teaching a smaller model

Knowledge distillation: teaching a smaller model

Train compact student models from large teachers with soft targets, generated data and careful evaluationAdvancedDeep learningNew
Magnus Eriksen$12
From Software Engineer to ML Engineer

From Software Engineer to ML Engineer

Use your engineering strengths to move into ML engineering with a focused plan for maths and MLAdvancedAI careersNew
Yohannes Tesfaye$11
Least Squares from First Principles

Least Squares from First Principles

Derive the normal equations, see regression as projection and solve it the stable wayAdvancedMath for AINew
Leandro Ferraz$10
Probability Puzzles and Paradoxes

Probability Puzzles and Paradoxes

Sharpen your reasoning with famous puzzles, then settle every argument by counting or simulatingAll levelsData science and statisticsNew
Kenta Arai$5
Sequential Testing and the Peeking Problem

Sequential Testing and the Peeking Problem

Monitor experiments early and often without inflating your false positive rateAdvancedData science and statisticsNew
Kojo Amankwah$11