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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#
  • Automated tests
  • AI code review
  • Community solutions
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AI Learning HubNeural networks, ML and LLMs from scratch Neural networks from scratchNeurons, backpropagation and optimizers Machine learning from scratchRegression, classification and clustering Transformers and LLMs from scratchTokenizers, attention and text generation Classical AI and reinforcement learningSearch, games and reinforcement learning
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42 challenges
Easy

Xavier and He Weight Initialization

Compute the range or standard deviation used to initialize the weights of a layer.

You'll learn Xavier and He initTraining stability
Neural networksaimachine learning
C# Python C++
0 solved
No solutions yet
Medium

Temperature and Top-K Sampling

Choose the next token like a language model does: keep the top k logits, apply temperature, and sample.

You'll learn Text generationSampling
aimachine learning
Python C++ C#
0 solved
No solutions yet
Medium

Train a Neuron with Gradient Descent

Repeat forward pass, gradients and weight updates to teach a sigmoid neuron from examples.

You'll learn Gradient descentTraining loops
Neural networksaimachine learning
Python C++ C#
0 solved
No solutions yet
Medium

Byte Pair Encoding (BPE) Merges

Learn subword merges the way GPT tokenizers do: repeatedly merge the most frequent pair of adjacent symbols.

You'll learn BPESubword tokenization
aimachine learning
Python C++ C#
0 solved
No solutions yet
Medium

Linear Regression with Gradient Descent

Learn the slope and intercept of a line by repeatedly stepping down the mean squared error.

You'll learn Gradient descentRegression
aimachine learning
Python C++ C#
0 solved
No solutions yet
Easy

One-Hot Encoding

Turn categories into vectors with a single 1, the input format for classifiers and embeddings.

You'll learn One-hot vectorsCategorical data
aimachine learning
Python C++ C#
0 solved
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
Python C++ C#
0 solved
No solutions yet
Easy

Gini Impurity

Measure how mixed the labels in a group are, the score decision trees use to choose splits.

You'll learn Decision treesImpurity measures
aimachine learning
Python C++ C#
0 solved
No solutions yet
Easy

Logistic Regression Prediction

Classify samples as 0 or 1 by passing a weighted sum through the sigmoid and comparing it to a threshold.

You'll learn Logistic regressionThresholds
aimachine learning
Python C++ C#
0 solved
No solutions yet
Medium

Simple Linear Regression (Least Squares)

Fit the best straight line through data points with the least squares formulas.

You'll learn Least squaresRegression
aimachine learning
Python C++ C#
0 solved
No solutions yet
Medium

Sinusoidal Positional Encoding

Compute the sine and cosine position vectors Transformers add to token embeddings.

You'll learn Positional encodingTrigonometry
aimachine learning
C# Python C++
0 solved
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
Python C++ C#
0 solved
No solutions yet
Medium

Naive Bayes Classifier

Predict a class from categorical features with Bayes' theorem and Laplace smoothing.

You'll learn Bayes' theoremLaplace smoothing
aimachine learning
Python C++ C#
0 solved
No solutions yet
Easy

Min-Max Normalization

Rescale a feature so its smallest value becomes 0 and its largest becomes 1.

You'll learn Feature scalingData preprocessing
aimachine learning
Python C++ C#
0 solved
No solutions yet
Easy

Softmax Function

Turn raw scores into probabilities that add up to 1, without overflowing on large values.

You'll learn SoftmaxNumerical stability
aimachine learning
Python C++ C#
0 solved
No solutions yet
Medium

K-Means Clustering

Group points into k clusters by repeatedly assigning them to the nearest centroid and moving the centroids.

You'll learn ClusteringCentroids
aimachine learning
Python C++ C#
0 solved
No solutions yet
Easy

Z-Score Standardization

Center a feature at 0 and scale it to a standard deviation of 1.

You'll learn StandardizationMean and std dev
aimachine learning
Python C++ C#
0 solved
No solutions yet
Medium

Causal (Masked) Self-Attention

Implement the masked attention GPT models use, where each token can only look at itself and earlier tokens.

You'll learn Masked attentionGPT models
aimachine learning
Python C++ C#
0 solved
No solutions yet

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