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AI Foundations tutorial

Data, regression, gradient descent, nearest neighbours, honest evaluation and retrieval, built from scratch in Python.

6 lessonsabout 9 h Learn first: Python from Zero

Learn it by doing

The interactive course has the same lessons with an editor next to them: run every example, answer the quizzes and solve exercises that are checked the moment you submit. Free to start, no sign-up.

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Learning from data

Prepare data, fit a line and train it with gradient descent.

1 Data, features and labelsHow does a program learn from examples instead of rules?2 Linear regression and lossHow do you find the best straight line through noisy points?3 Gradient descentHow does a model improve itself step by step?

Models in practice

Classify with neighbours, measure honestly and retrieve with embeddings.

4 k-nearest neighboursHow can a program label something new by looking at similar examples?5 Measuring a modelYour model is 95% accurate. Is it any good?6 Embeddings and retrievalHow does an AI assistant find the right document to answer your question?