Exercises

  • This page provides a comprehensive list of exercises for Google's Machine Learning Crash Course, categorized by topic and exercise type.

  • The exercises include programming exercises, interactive exercises, and quizzes, designed to reinforce key machine learning concepts.

  • Programming exercises utilize the Colaboratory platform, enabling users to run code directly in their browser without any setup.

  • The exercises cover a wide range of topics including linear regression, logistic regression, classification, working with numerical and categorical data, datasets and overfitting, neural networks, embeddings, large language models, production ML systems, and fairness.

  • These exercises offer practical, hands-on experience with fundamental machine learning techniques and considerations.

This page lists the exercises in Machine Learning Crash Course.

Programming exercises run directly in your browser (no setup required!) using the Colaboratory platform. Colaboratory is supported on most major browsers, and is most thoroughly tested on desktop versions of Chrome and Firefox.

All

Linear regression

Logistic regression

Classification

Working with numerical data

Working with categorical data

Datasets, generalization, and overfitting

Neural networks

Embeddings

Large language models

Production ML systems

Fairness

Quizzes

Linear regression

Logistic regression

Classification

Working with numerical data

Working with categorical data

Datasets, generalization, and overfitting

Neural networks

Embeddings

Large language models

Production ML systems

Fairness

Interactive

Linear regression

Logistic regression

Classification

Working with numerical data

Working with categorical data

Datasets, generalization, and overfitting

Neural networks

Embeddings

Large language models

Production ML systems

Fairness

Programming

Linear regression

Logistic regression

Classification

Working with numerical data

Working with categorical data

Datasets, generalization, and overfitting

Neural networks

Embeddings

Large language models

Production ML systems

Fairness

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Prerequisites
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Linear regression (10 min)