# Exercises

<br />

This page lists the exercises in Machine Learning Crash Course.

Programming exercises run directly in your browser (no setup
required!) using the [Colaboratory](https://colab.research.google.com)
platform. Colaboratory is supported on most major browsers, and is most
thoroughly tested on desktop versions of Chrome and Firefox.

### All

## Linear regression

- [Check your understanding: Intro to linear regression](https://developers.google.com/machine-learning/crash-course/linear-regression#exercise_check_your_understanding)
- [Check your understanding: Loss](https://developers.google.com/machine-learning/crash-course/linear-regression/loss#check-your-understanding)
- [Interactive: Linear regression parameters](https://developers.google.com/machine-learning/crash-course/linear-regression/parameters-exercise)
- [Check your understanding: Gradient descent](https://developers.google.com/machine-learning/crash-course/linear-regression/gradient-descent#exercise_check_your_understanding)
- [Check your understanding: Learning rate](https://developers.google.com/machine-learning/crash-course/linear-regression/hyperparameters#exercise_check_your_understanding)
- [Check your understanding: Batch size](https://developers.google.com/machine-learning/crash-course/linear-regression/hyperparameters#exercise_check_your_understanding_2)
- [Interactive: Gradient descent](https://developers.google.com/machine-learning/crash-course/linear-regression/gradient-descent-exercise)
- [Programming: Linear regression](https://developers.google.com/machine-learning/crash-course/linear-regression/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/linear-regression/test-your-knowledge)

## Logistic regression

- [Check your understanding: Calculating a probability](https://developers.google.com/machine-learning/crash-course/logistic-regression/sigmoid-function#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/logistic-regression/test-your-knowledge)

## Classification

- [Interactive: Thresholding](https://developers.google.com/machine-learning/crash-course/classification/thresholding#effect_of_threshold_on_true_and_false_positives_and_negatives)
- [Check your understanding: TP, TN, FP, FN](https://developers.google.com/machine-learning/crash-course/classification/thresholding#check_your_understanding)
- [Interactive: Precision and recall](https://developers.google.com/machine-learning/crash-course/classification/accuracy-precision-recall#precision)
- [Check your understanding: Precision and recall](https://developers.google.com/machine-learning/crash-course/classification/accuracy-precision-recall#exercise_check_your_understanding)
- [Interactive: ROC curve](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc#auc_and_roc_for_choosing_model_and_threshold)
- [Check your understanding: ROC and AUC](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc#exercise_check_your_understanding)
- [Programming: Classification](https://developers.google.com/machine-learning/crash-course/classification/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/classification/test-your-knowledge)

## Working with numerical data

- [Programming: Statistics and bad values](https://developers.google.com/machine-learning/crash-course/numerical-data/programming-exercises)
- [Check your understanding: Linear scaling](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_check_your_understanding)
- [Check your understanding: Z-score scaling](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_check_your_understanding_2)
- [Test your knowledge: Normalization techniques](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_test_your_knowledge)
- [Check your understanding: Binning](https://developers.google.com/machine-learning/crash-course/numerical-data/binning#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/numerical-data/test-your-knowledge)

## Working with categorical data

- [Check your intuition: Encoding](https://developers.google.com/machine-learning/crash-course/categorical-data/one-hot-encoding#exercise_check_your_intuition)
- [Check your intuition: Index numbers](https://developers.google.com/machine-learning/crash-course/categorical-data/one-hot-encoding#exercise_check_your_intuition_2)
- [Interactive: Feature crosses](https://developers.google.com/machine-learning/crash-course/categorical-data/feature-cross-exercises)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/categorical-data/test-your-knowledge)

## Datasets, generalization, and overfitting

- [Check your intuition: Introduction](https://developers.google.com/machine-learning/crash-course/overfitting#introduction)
- [Check your understanding: Imputation](https://developers.google.com/machine-learning/crash-course/overfitting/data-characteristics#exercise_check_your_understanding)
- [Check your understanding: Proxy labels](https://developers.google.com/machine-learning/crash-course/overfitting/labels#exercise_check_your_understanding)
- [Check your understanding: Imbalanced datasets](https://developers.google.com/machine-learning/crash-course/overfitting/imbalanced-datasets#exercise_check_your_understanding)
- [Check your intuition: Dividing datasets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercise_check_your_intuition)
- [Check your intuition: Test sets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercise_check_your_intuition_2)
- [Check your understanding: Dividing datasets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercises_check_your_understanding)
- [Check your understanding: Overfitting](https://developers.google.com/machine-learning/crash-course/overfitting/overfitting#exercises_check_your_understanding)
- [Check your understanding: Model complexity](https://developers.google.com/machine-learning/crash-course/overfitting/model-complexity#exercises_check_your_understanding)
- [Check your intuition: Complexity metrics](https://developers.google.com/machine-learning/crash-course/overfitting/model-complexity#exercise_check_your_intuition)
- [Check your understanding: L~2~ regularization](https://developers.google.com/machine-learning/crash-course/overfitting/regularization#exercises_check_your_understanding)
- [Interpreting loss curves](https://developers.google.com/machine-learning/crash-course/overfitting/interpreting-loss-curves)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/overfitting/test-your-knowledge)

## Neural networks

- [Interactive: Input layer and output layer](https://developers.google.com/machine-learning/crash-course/neural-networks/nodes-hidden-layers#exercise_1)
- [Interactive: Adding a hidden layer](https://developers.google.com/machine-learning/crash-course/neural-networks/nodes-hidden-layers#exercise_2)
- [Interactive: Activation functions](https://developers.google.com/machine-learning/crash-course/neural-networks/activation-functions)
- [Interactive: Modifying the neural network configuration](https://developers.google.com/machine-learning/crash-course/neural-networks/interactive-exercises#exercise_1)
- [Interactive: Training a neural network](https://developers.google.com/machine-learning/crash-course/neural-networks/interactive-exercises#exercise_2)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/neural-networks/test-your-knowledge)

## Embeddings

- [Interactive: Exploring a word2vec visualization](https://developers.google.com/machine-learning/crash-course/embeddings/embedding-space#exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/embeddings/test-your-knowledge)

## Large language models

- [Check your understanding: n-grams](https://developers.google.com/machine-learning/crash-course/llm#exercise_check_your_understanding)
- [Check your understanding: Transformers](https://developers.google.com/machine-learning/crash-course/llm/transformers#exercise_check_your_understanding)
- [Check your understanding: Fine-tuning and distillation](https://developers.google.com/machine-learning/crash-course/llm/tuning#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/llm/test-your-knowledge)

## Production ML systems

- [Check your understanding: Static vs. dynamic training](https://developers.google.com/machine-learning/crash-course/production-ml-systems/static-vs-dynamic-training#exercises_check_your_understanding)
- [Check your understanding: Static vs. dynamic inference](https://developers.google.com/machine-learning/crash-course/production-ml-systems/static-vs-dynamic-inference#exercises_check_your_understanding)
- [Check your understanding: Real-world metrics](https://developers.google.com/machine-learning/crash-course/production-ml-systems/monitoring#exercise_check_your_understanding)
- [Check your understanding: Label leakage](https://developers.google.com/machine-learning/crash-course/production-ml-systems/monitoring#exercise_check_your_understanding_2)
- [Check your understanding: Feedback loops](https://developers.google.com/machine-learning/crash-course/production-ml-systems/questions#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/production-ml-systems/test-your-knowledge)

## Fairness

- [Check your understanding: Types of bias](https://developers.google.com/machine-learning/crash-course/fairness/types-of-bias#exercise_check_your_understanding)
- [Check your understanding: Missing feature values](https://developers.google.com/machine-learning/crash-course/fairness/identifying-bias#exercise_check_your_understanding)
- [Check your understanding: Unexpected feature values](https://developers.google.com/machine-learning/crash-course/fairness/identifying-bias#exercise_check_your_understanding_2)
- [Check your understanding: Mitigating bias](https://developers.google.com/machine-learning/crash-course/fairness/mitigating-bias#exercise_check_your_understanding)
- [Check your intuition: Demographic parity](https://developers.google.com/machine-learning/crash-course/fairness/demographic-parity#exercise_check_your_intuition)
- [Check your understanding: Equality of opportunity](https://developers.google.com/machine-learning/crash-course/fairness/equality-of-opportunity#exercise_check_your_understanding)
- [Check your understanding: Counterfactual fairness](https://developers.google.com/machine-learning/crash-course/fairness/counterfactual-fairness#exercise_check_your_understanding)
- [Programming: Addressing bias and fairness issues](https://developers.google.com/machine-learning/crash-course/fairness/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/fairness/test-your-knowledge)

### Quizzes

## Linear regression

- [Check your understanding: Intro to linear regression](https://developers.google.com/machine-learning/crash-course/linear-regression#exercise_check_your_understanding)
- [Check your understanding: Loss](https://developers.google.com/machine-learning/crash-course/linear-regression/loss#check-your-understanding)
- [Interactive: Linear regression parameters](https://developers.google.com/machine-learning/crash-course/linear-regression/parameters-exercise)
- [Check your understanding: Gradient descent](https://developers.google.com/machine-learning/crash-course/linear-regression/gradient-descent#exercise_check_your_understanding)
- [Check your understanding: Learning rate](https://developers.google.com/machine-learning/crash-course/linear-regression/hyperparameters#exercise_check_your_understanding)
- [Check your understanding: Batch size](https://developers.google.com/machine-learning/crash-course/linear-regression/hyperparameters#exercise_check_your_understanding_2)
- [Interactive: Gradient descent](https://developers.google.com/machine-learning/crash-course/linear-regression/gradient-descent-exercise)
- [Programming: Linear regression](https://developers.google.com/machine-learning/crash-course/linear-regression/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/linear-regression/test-your-knowledge)

## Logistic regression

- [Check your understanding: Calculating a probability](https://developers.google.com/machine-learning/crash-course/logistic-regression/sigmoid-function#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/logistic-regression/test-your-knowledge)

## Classification

- [Interactive: Thresholding](https://developers.google.com/machine-learning/crash-course/classification/thresholding#effect_of_threshold_on_true_and_false_positives_and_negatives)
- [Check your understanding: TP, TN, FP, FN](https://developers.google.com/machine-learning/crash-course/classification/thresholding#check_your_understanding)
- [Interactive: Precision and recall](https://developers.google.com/machine-learning/crash-course/classification/accuracy-precision-recall#precision)
- [Check your understanding: Precision and recall](https://developers.google.com/machine-learning/crash-course/classification/accuracy-precision-recall#exercise_check_your_understanding)
- [Interactive: ROC curve](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc#auc_and_roc_for_choosing_model_and_threshold)
- [Check your understanding: ROC and AUC](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc#exercise_check_your_understanding)
- [Programming: Classification](https://developers.google.com/machine-learning/crash-course/classification/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/classification/test-your-knowledge)

## Working with numerical data

- [Programming: Statistics and bad values](https://developers.google.com/machine-learning/crash-course/numerical-data/programming-exercises)
- [Check your understanding: Linear scaling](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_check_your_understanding)
- [Check your understanding: Z-score scaling](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_check_your_understanding_2)
- [Test your knowledge: Normalization techniques](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_test_your_knowledge)
- [Check your understanding: Binning](https://developers.google.com/machine-learning/crash-course/numerical-data/binning#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/numerical-data/test-your-knowledge)

## Working with categorical data

- [Check your intuition: Encoding](https://developers.google.com/machine-learning/crash-course/categorical-data/one-hot-encoding#exercise_check_your_intuition)
- [Check your intuition: Index numbers](https://developers.google.com/machine-learning/crash-course/categorical-data/one-hot-encoding#exercise_check_your_intuition_2)
- [Interactive: Feature crosses](https://developers.google.com/machine-learning/crash-course/categorical-data/feature-cross-exercises)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/categorical-data/test-your-knowledge)

## Datasets, generalization, and overfitting

- [Check your intuition: Introduction](https://developers.google.com/machine-learning/crash-course/overfitting#introduction)
- [Check your understanding: Imputation](https://developers.google.com/machine-learning/crash-course/overfitting/data-characteristics#exercise_check_your_understanding)
- [Check your understanding: Proxy labels](https://developers.google.com/machine-learning/crash-course/overfitting/labels#exercise_check_your_understanding)
- [Check your understanding: Imbalanced datasets](https://developers.google.com/machine-learning/crash-course/overfitting/imbalanced-datasets#exercise_check_your_understanding)
- [Check your intuition: Dividing datasets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercise_check_your_intuition)
- [Check your intuition: Test sets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercise_check_your_intuition_2)
- [Check your understanding: Dividing datasets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercises_check_your_understanding)
- [Check your understanding: Overfitting](https://developers.google.com/machine-learning/crash-course/overfitting/overfitting#exercises_check_your_understanding)
- [Check your understanding: Model complexity](https://developers.google.com/machine-learning/crash-course/overfitting/model-complexity#exercises_check_your_understanding)
- [Check your intuition: Complexity metrics](https://developers.google.com/machine-learning/crash-course/overfitting/model-complexity#exercise_check_your_intuition)
- [Check your understanding: L~2~ regularization](https://developers.google.com/machine-learning/crash-course/overfitting/regularization#exercises_check_your_understanding)
- [Interpreting loss curves](https://developers.google.com/machine-learning/crash-course/overfitting/interpreting-loss-curves)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/overfitting/test-your-knowledge)

## Neural networks

- [Interactive: Input layer and output layer](https://developers.google.com/machine-learning/crash-course/neural-networks/nodes-hidden-layers#exercise_1)
- [Interactive: Adding a hidden layer](https://developers.google.com/machine-learning/crash-course/neural-networks/nodes-hidden-layers#exercise_2)
- [Interactive: Activation functions](https://developers.google.com/machine-learning/crash-course/neural-networks/activation-functions)
- [Interactive: Modifying the neural network configuration](https://developers.google.com/machine-learning/crash-course/neural-networks/interactive-exercises#exercise_1)
- [Interactive: Training a neural network](https://developers.google.com/machine-learning/crash-course/neural-networks/interactive-exercises#exercise_2)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/neural-networks/test-your-knowledge)

## Embeddings

- [Interactive: Exploring a word2vec visualization](https://developers.google.com/machine-learning/crash-course/embeddings/embedding-space#exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/embeddings/test-your-knowledge)

## Large language models

- [Check your understanding: n-grams](https://developers.google.com/machine-learning/crash-course/llm#exercise_check_your_understanding)
- [Check your understanding: Transformers](https://developers.google.com/machine-learning/crash-course/llm/transformers#exercise_check_your_understanding)
- [Check your understanding: Fine-tuning and distillation](https://developers.google.com/machine-learning/crash-course/llm/tuning#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/llm/test-your-knowledge)

## Production ML systems

- [Check your understanding: Static vs. dynamic training](https://developers.google.com/machine-learning/crash-course/production-ml-systems/static-vs-dynamic-training#exercises_check_your_understanding)
- [Check your understanding: Static vs. dynamic inference](https://developers.google.com/machine-learning/crash-course/production-ml-systems/static-vs-dynamic-inference#exercises_check_your_understanding)
- [Check your understanding: Real-world metrics](https://developers.google.com/machine-learning/crash-course/production-ml-systems/monitoring#exercise_check_your_understanding)
- [Check your understanding: Label leakage](https://developers.google.com/machine-learning/crash-course/production-ml-systems/monitoring#exercise_check_your_understanding_2)
- [Check your understanding: Feedback loops](https://developers.google.com/machine-learning/crash-course/production-ml-systems/questions#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/production-ml-systems/test-your-knowledge)

## Fairness

- [Check your understanding: Types of bias](https://developers.google.com/machine-learning/crash-course/fairness/types-of-bias#exercise_check_your_understanding)
- [Check your understanding: Missing feature values](https://developers.google.com/machine-learning/crash-course/fairness/identifying-bias#exercise_check_your_understanding)
- [Check your understanding: Unexpected feature values](https://developers.google.com/machine-learning/crash-course/fairness/identifying-bias#exercise_check_your_understanding_2)
- [Check your understanding: Mitigating bias](https://developers.google.com/machine-learning/crash-course/fairness/mitigating-bias#exercise_check_your_understanding)
- [Check your intuition: Demographic parity](https://developers.google.com/machine-learning/crash-course/fairness/demographic-parity#exercise_check_your_intuition)
- [Check your understanding: Equality of opportunity](https://developers.google.com/machine-learning/crash-course/fairness/equality-of-opportunity#exercise_check_your_understanding)
- [Check your understanding: Counterfactual fairness](https://developers.google.com/machine-learning/crash-course/fairness/counterfactual-fairness#exercise_check_your_understanding)
- [Programming: Addressing bias and fairness issues](https://developers.google.com/machine-learning/crash-course/fairness/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/fairness/test-your-knowledge)

### Interactive

## Linear regression

- [Check your understanding: Intro to linear regression](https://developers.google.com/machine-learning/crash-course/linear-regression#exercise_check_your_understanding)
- [Check your understanding: Loss](https://developers.google.com/machine-learning/crash-course/linear-regression/loss#check-your-understanding)
- [Interactive: Linear regression parameters](https://developers.google.com/machine-learning/crash-course/linear-regression/parameters-exercise)
- [Check your understanding: Gradient descent](https://developers.google.com/machine-learning/crash-course/linear-regression/gradient-descent#exercise_check_your_understanding)
- [Check your understanding: Learning rate](https://developers.google.com/machine-learning/crash-course/linear-regression/hyperparameters#exercise_check_your_understanding)
- [Check your understanding: Batch size](https://developers.google.com/machine-learning/crash-course/linear-regression/hyperparameters#exercise_check_your_understanding_2)
- [Interactive: Gradient descent](https://developers.google.com/machine-learning/crash-course/linear-regression/gradient-descent-exercise)
- [Programming: Linear regression](https://developers.google.com/machine-learning/crash-course/linear-regression/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/linear-regression/test-your-knowledge)

## Logistic regression

- [Check your understanding: Calculating a probability](https://developers.google.com/machine-learning/crash-course/logistic-regression/sigmoid-function#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/logistic-regression/test-your-knowledge)

## Classification

- [Interactive: Thresholding](https://developers.google.com/machine-learning/crash-course/classification/thresholding#effect_of_threshold_on_true_and_false_positives_and_negatives)
- [Check your understanding: TP, TN, FP, FN](https://developers.google.com/machine-learning/crash-course/classification/thresholding#check_your_understanding)
- [Interactive: Precision and recall](https://developers.google.com/machine-learning/crash-course/classification/accuracy-precision-recall#precision)
- [Check your understanding: Precision and recall](https://developers.google.com/machine-learning/crash-course/classification/accuracy-precision-recall#exercise_check_your_understanding)
- [Interactive: ROC curve](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc#auc_and_roc_for_choosing_model_and_threshold)
- [Check your understanding: ROC and AUC](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc#exercise_check_your_understanding)
- [Programming: Classification](https://developers.google.com/machine-learning/crash-course/classification/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/classification/test-your-knowledge)

## Working with numerical data

- [Programming: Statistics and bad values](https://developers.google.com/machine-learning/crash-course/numerical-data/programming-exercises)
- [Check your understanding: Linear scaling](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_check_your_understanding)
- [Check your understanding: Z-score scaling](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_check_your_understanding_2)
- [Test your knowledge: Normalization techniques](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_test_your_knowledge)
- [Check your understanding: Binning](https://developers.google.com/machine-learning/crash-course/numerical-data/binning#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/numerical-data/test-your-knowledge)

## Working with categorical data

- [Check your intuition: Encoding](https://developers.google.com/machine-learning/crash-course/categorical-data/one-hot-encoding#exercise_check_your_intuition)
- [Check your intuition: Index numbers](https://developers.google.com/machine-learning/crash-course/categorical-data/one-hot-encoding#exercise_check_your_intuition_2)
- [Interactive: Feature crosses](https://developers.google.com/machine-learning/crash-course/categorical-data/feature-cross-exercises)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/categorical-data/test-your-knowledge)

## Datasets, generalization, and overfitting

- [Check your intuition: Introduction](https://developers.google.com/machine-learning/crash-course/overfitting#introduction)
- [Check your understanding: Imputation](https://developers.google.com/machine-learning/crash-course/overfitting/data-characteristics#exercise_check_your_understanding)
- [Check your understanding: Proxy labels](https://developers.google.com/machine-learning/crash-course/overfitting/labels#exercise_check_your_understanding)
- [Check your understanding: Imbalanced datasets](https://developers.google.com/machine-learning/crash-course/overfitting/imbalanced-datasets#exercise_check_your_understanding)
- [Check your intuition: Dividing datasets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercise_check_your_intuition)
- [Check your intuition: Test sets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercise_check_your_intuition_2)
- [Check your understanding: Dividing datasets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercises_check_your_understanding)
- [Check your understanding: Overfitting](https://developers.google.com/machine-learning/crash-course/overfitting/overfitting#exercises_check_your_understanding)
- [Check your understanding: Model complexity](https://developers.google.com/machine-learning/crash-course/overfitting/model-complexity#exercises_check_your_understanding)
- [Check your intuition: Complexity metrics](https://developers.google.com/machine-learning/crash-course/overfitting/model-complexity#exercise_check_your_intuition)
- [Check your understanding: L~2~ regularization](https://developers.google.com/machine-learning/crash-course/overfitting/regularization#exercises_check_your_understanding)
- [Interpreting loss curves](https://developers.google.com/machine-learning/crash-course/overfitting/interpreting-loss-curves)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/overfitting/test-your-knowledge)

## Neural networks

- [Interactive: Input layer and output layer](https://developers.google.com/machine-learning/crash-course/neural-networks/nodes-hidden-layers#exercise_1)
- [Interactive: Adding a hidden layer](https://developers.google.com/machine-learning/crash-course/neural-networks/nodes-hidden-layers#exercise_2)
- [Interactive: Activation functions](https://developers.google.com/machine-learning/crash-course/neural-networks/activation-functions)
- [Interactive: Modifying the neural network configuration](https://developers.google.com/machine-learning/crash-course/neural-networks/interactive-exercises#exercise_1)
- [Interactive: Training a neural network](https://developers.google.com/machine-learning/crash-course/neural-networks/interactive-exercises#exercise_2)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/neural-networks/test-your-knowledge)

## Embeddings

- [Interactive: Exploring a word2vec visualization](https://developers.google.com/machine-learning/crash-course/embeddings/embedding-space#exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/embeddings/test-your-knowledge)

## Large language models

- [Check your understanding: n-grams](https://developers.google.com/machine-learning/crash-course/llm#exercise_check_your_understanding)
- [Check your understanding: Transformers](https://developers.google.com/machine-learning/crash-course/llm/transformers#exercise_check_your_understanding)
- [Check your understanding: Fine-tuning and distillation](https://developers.google.com/machine-learning/crash-course/llm/tuning#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/llm/test-your-knowledge)

## Production ML systems

- [Check your understanding: Static vs. dynamic training](https://developers.google.com/machine-learning/crash-course/production-ml-systems/static-vs-dynamic-training#exercises_check_your_understanding)
- [Check your understanding: Static vs. dynamic inference](https://developers.google.com/machine-learning/crash-course/production-ml-systems/static-vs-dynamic-inference#exercises_check_your_understanding)
- [Check your understanding: Real-world metrics](https://developers.google.com/machine-learning/crash-course/production-ml-systems/monitoring#exercise_check_your_understanding)
- [Check your understanding: Label leakage](https://developers.google.com/machine-learning/crash-course/production-ml-systems/monitoring#exercise_check_your_understanding_2)
- [Check your understanding: Feedback loops](https://developers.google.com/machine-learning/crash-course/production-ml-systems/questions#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/production-ml-systems/test-your-knowledge)

## Fairness

- [Check your understanding: Types of bias](https://developers.google.com/machine-learning/crash-course/fairness/types-of-bias#exercise_check_your_understanding)
- [Check your understanding: Missing feature values](https://developers.google.com/machine-learning/crash-course/fairness/identifying-bias#exercise_check_your_understanding)
- [Check your understanding: Unexpected feature values](https://developers.google.com/machine-learning/crash-course/fairness/identifying-bias#exercise_check_your_understanding_2)
- [Check your understanding: Mitigating bias](https://developers.google.com/machine-learning/crash-course/fairness/mitigating-bias#exercise_check_your_understanding)
- [Check your intuition: Demographic parity](https://developers.google.com/machine-learning/crash-course/fairness/demographic-parity#exercise_check_your_intuition)
- [Check your understanding: Equality of opportunity](https://developers.google.com/machine-learning/crash-course/fairness/equality-of-opportunity#exercise_check_your_understanding)
- [Check your understanding: Counterfactual fairness](https://developers.google.com/machine-learning/crash-course/fairness/counterfactual-fairness#exercise_check_your_understanding)
- [Programming: Addressing bias and fairness issues](https://developers.google.com/machine-learning/crash-course/fairness/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/fairness/test-your-knowledge)

### Programming

## Linear regression

- [Check your understanding: Intro to linear regression](https://developers.google.com/machine-learning/crash-course/linear-regression#exercise_check_your_understanding)
- [Check your understanding: Loss](https://developers.google.com/machine-learning/crash-course/linear-regression/loss#check-your-understanding)
- [Interactive: Linear regression parameters](https://developers.google.com/machine-learning/crash-course/linear-regression/parameters-exercise)
- [Check your understanding: Gradient descent](https://developers.google.com/machine-learning/crash-course/linear-regression/gradient-descent#exercise_check_your_understanding)
- [Check your understanding: Learning rate](https://developers.google.com/machine-learning/crash-course/linear-regression/hyperparameters#exercise_check_your_understanding)
- [Check your understanding: Batch size](https://developers.google.com/machine-learning/crash-course/linear-regression/hyperparameters#exercise_check_your_understanding_2)
- [Interactive: Gradient descent](https://developers.google.com/machine-learning/crash-course/linear-regression/gradient-descent-exercise)
- [Programming: Linear regression](https://developers.google.com/machine-learning/crash-course/linear-regression/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/linear-regression/test-your-knowledge)

## Logistic regression

- [Check your understanding: Calculating a probability](https://developers.google.com/machine-learning/crash-course/logistic-regression/sigmoid-function#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/logistic-regression/test-your-knowledge)

## Classification

- [Interactive: Thresholding](https://developers.google.com/machine-learning/crash-course/classification/thresholding#effect_of_threshold_on_true_and_false_positives_and_negatives)
- [Check your understanding: TP, TN, FP, FN](https://developers.google.com/machine-learning/crash-course/classification/thresholding#check_your_understanding)
- [Interactive: Precision and recall](https://developers.google.com/machine-learning/crash-course/classification/accuracy-precision-recall#precision)
- [Check your understanding: Precision and recall](https://developers.google.com/machine-learning/crash-course/classification/accuracy-precision-recall#exercise_check_your_understanding)
- [Interactive: ROC curve](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc#auc_and_roc_for_choosing_model_and_threshold)
- [Check your understanding: ROC and AUC](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc#exercise_check_your_understanding)
- [Programming: Classification](https://developers.google.com/machine-learning/crash-course/classification/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/classification/test-your-knowledge)

## Working with numerical data

- [Programming: Statistics and bad values](https://developers.google.com/machine-learning/crash-course/numerical-data/programming-exercises)
- [Check your understanding: Linear scaling](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_check_your_understanding)
- [Check your understanding: Z-score scaling](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_check_your_understanding_2)
- [Test your knowledge: Normalization techniques](https://developers.google.com/machine-learning/crash-course/numerical-data/normalization#exercise_test_your_knowledge)
- [Check your understanding: Binning](https://developers.google.com/machine-learning/crash-course/numerical-data/binning#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/numerical-data/test-your-knowledge)

## Working with categorical data

- [Check your intuition: Encoding](https://developers.google.com/machine-learning/crash-course/categorical-data/one-hot-encoding#exercise_check_your_intuition)
- [Check your intuition: Index numbers](https://developers.google.com/machine-learning/crash-course/categorical-data/one-hot-encoding#exercise_check_your_intuition_2)
- [Interactive: Feature crosses](https://developers.google.com/machine-learning/crash-course/categorical-data/feature-cross-exercises)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/categorical-data/test-your-knowledge)

## Datasets, generalization, and overfitting

- [Check your intuition: Introduction](https://developers.google.com/machine-learning/crash-course/overfitting#introduction)
- [Check your understanding: Imputation](https://developers.google.com/machine-learning/crash-course/overfitting/data-characteristics#exercise_check_your_understanding)
- [Check your understanding: Proxy labels](https://developers.google.com/machine-learning/crash-course/overfitting/labels#exercise_check_your_understanding)
- [Check your understanding: Imbalanced datasets](https://developers.google.com/machine-learning/crash-course/overfitting/imbalanced-datasets#exercise_check_your_understanding)
- [Check your intuition: Dividing datasets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercise_check_your_intuition)
- [Check your intuition: Test sets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercise_check_your_intuition_2)
- [Check your understanding: Dividing datasets](https://developers.google.com/machine-learning/crash-course/overfitting/dividing-datasets#exercises_check_your_understanding)
- [Check your understanding: Overfitting](https://developers.google.com/machine-learning/crash-course/overfitting/overfitting#exercises_check_your_understanding)
- [Check your understanding: Model complexity](https://developers.google.com/machine-learning/crash-course/overfitting/model-complexity#exercises_check_your_understanding)
- [Check your intuition: Complexity metrics](https://developers.google.com/machine-learning/crash-course/overfitting/model-complexity#exercise_check_your_intuition)
- [Check your understanding: L~2~ regularization](https://developers.google.com/machine-learning/crash-course/overfitting/regularization#exercises_check_your_understanding)
- [Interpreting loss curves](https://developers.google.com/machine-learning/crash-course/overfitting/interpreting-loss-curves)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/overfitting/test-your-knowledge)

## Neural networks

- [Interactive: Input layer and output layer](https://developers.google.com/machine-learning/crash-course/neural-networks/nodes-hidden-layers#exercise_1)
- [Interactive: Adding a hidden layer](https://developers.google.com/machine-learning/crash-course/neural-networks/nodes-hidden-layers#exercise_2)
- [Interactive: Activation functions](https://developers.google.com/machine-learning/crash-course/neural-networks/activation-functions)
- [Interactive: Modifying the neural network configuration](https://developers.google.com/machine-learning/crash-course/neural-networks/interactive-exercises#exercise_1)
- [Interactive: Training a neural network](https://developers.google.com/machine-learning/crash-course/neural-networks/interactive-exercises#exercise_2)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/neural-networks/test-your-knowledge)

## Embeddings

- [Interactive: Exploring a word2vec visualization](https://developers.google.com/machine-learning/crash-course/embeddings/embedding-space#exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/embeddings/test-your-knowledge)

## Large language models

- [Check your understanding: n-grams](https://developers.google.com/machine-learning/crash-course/llm#exercise_check_your_understanding)
- [Check your understanding: Transformers](https://developers.google.com/machine-learning/crash-course/llm/transformers#exercise_check_your_understanding)
- [Check your understanding: Fine-tuning and distillation](https://developers.google.com/machine-learning/crash-course/llm/tuning#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/llm/test-your-knowledge)

## Production ML systems

- [Check your understanding: Static vs. dynamic training](https://developers.google.com/machine-learning/crash-course/production-ml-systems/static-vs-dynamic-training#exercises_check_your_understanding)
- [Check your understanding: Static vs. dynamic inference](https://developers.google.com/machine-learning/crash-course/production-ml-systems/static-vs-dynamic-inference#exercises_check_your_understanding)
- [Check your understanding: Real-world metrics](https://developers.google.com/machine-learning/crash-course/production-ml-systems/monitoring#exercise_check_your_understanding)
- [Check your understanding: Label leakage](https://developers.google.com/machine-learning/crash-course/production-ml-systems/monitoring#exercise_check_your_understanding_2)
- [Check your understanding: Feedback loops](https://developers.google.com/machine-learning/crash-course/production-ml-systems/questions#exercise_check_your_understanding)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/production-ml-systems/test-your-knowledge)

## Fairness

- [Check your understanding: Types of bias](https://developers.google.com/machine-learning/crash-course/fairness/types-of-bias#exercise_check_your_understanding)
- [Check your understanding: Missing feature values](https://developers.google.com/machine-learning/crash-course/fairness/identifying-bias#exercise_check_your_understanding)
- [Check your understanding: Unexpected feature values](https://developers.google.com/machine-learning/crash-course/fairness/identifying-bias#exercise_check_your_understanding_2)
- [Check your understanding: Mitigating bias](https://developers.google.com/machine-learning/crash-course/fairness/mitigating-bias#exercise_check_your_understanding)
- [Check your intuition: Demographic parity](https://developers.google.com/machine-learning/crash-course/fairness/demographic-parity#exercise_check_your_intuition)
- [Check your understanding: Equality of opportunity](https://developers.google.com/machine-learning/crash-course/fairness/equality-of-opportunity#exercise_check_your_understanding)
- [Check your understanding: Counterfactual fairness](https://developers.google.com/machine-learning/crash-course/fairness/counterfactual-fairness#exercise_check_your_understanding)
- [Programming: Addressing bias and fairness issues](https://developers.google.com/machine-learning/crash-course/fairness/programming-exercise)
- [Final quiz: Test your knowledge](https://developers.google.com/machine-learning/crash-course/fairness/test-your-knowledge)