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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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- 226
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All challenges
Search by topic, language, or difficulty.
Easy
Matrix Multiplication
Multiply two matrices, the operation behind every layer of a neural network.
You'll learn
MatricesLinear algebra
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
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
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
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
Hard
Scaled Dot-Product Attention
Implement the attention operation at the heart of Transformers and large language models.
You'll learn
AttentionTransformers
No solutions yet
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