Machine learning coding challenges

Practise machine learning with 42 coding challenges, from easy to hard. Every challenge runs in your browser with instant tests, an AI review of your code and community solutions to compare.

Easy · 18 Medium · 20 Hard · 4

Skills you'll practise: Gradient descentBackpropagationChain ruleDecision treesRegressionTransformersActivationsAdamAttentionBPEBanditsBayes' theorem
  • Python · C++ · C#
  • Automated tests
  • AI code review
  • Community solutions
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42 challenges
Easy

Matrix Multiplication

Multiply two matrices, the operation behind every layer of a neural network.

You'll learn MatricesLinear algebra
aimachine learning
No solutions yet
Easy

Categorical Cross-Entropy Loss

Measure the loss of a multi-class classifier from its predicted probabilities and the true classes.

You'll learn Classification lossLogarithms
aimachine learning
No solutions yet
Easy

Cosine Similarity

Measure how similar two vectors are by the angle between them, as search engines do with embeddings.

You'll learn Vector similarityEmbeddings
aimachine learning
No solutions yet
Easy

Word Tokenizer and Vocabulary

Split text into lowercase words and build a vocabulary sorted by frequency, the first step of any language model.

You'll learn TokenizationVocabulary building
aimachine learning
No solutions yet
Easy

Dot Product of Two Vectors

Multiply two vectors element by element and add the results: the core operation of every neuron.

You'll learn VectorsDot product
Neural networksaimachine learning
Hard

Scaled Dot-Product Attention

Implement the attention operation at the heart of Transformers and large language models.

You'll learn AttentionTransformers
aimachine learning
No solutions yet