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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#
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All challenges
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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
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Easy
Matrix Multiplication
Multiply two matrices, the operation behind every layer of a neural network.
You'll learn
MatricesLinear algebra
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Medium
Information Gain
Compute how much splitting on a feature reduces entropy, the criterion behind ID3 decision trees.
You'll learn
EntropyDecision trees
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Medium
K-Nearest Neighbors Classifier
Predict a label by majority vote of the k closest training points.
You'll learn
KNNDistance metrics
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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
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Hard
Scaled Dot-Product Attention
Implement the attention operation at the heart of Transformers and large language models.
You'll learn
AttentionTransformers
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