# Machine learning crash course

> Fast-paced, practical introduction to machine learning, featuring a series of lessons with video lectures, interactive visualizations, and hands-on practice exercises, provided by Google

Fast-paced, practical introduction to [machine learning](https://wiki.g15e.com/pages/Machine%20learning.txt), featuring a series of lessons with video lectures, interactive visualizations, and hands-on practice exercises, provided by [Google](https://wiki.g15e.com/pages/Google.txt)

https://developers.google.com/machine-learning/crash-course

## Part 1. ML models

- Chapter 1. [Linear regression](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Linear%20regression.txt)
- Chapter 2. [Logistic regression](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Logistic%20regression.txt)
- Chapter 3. [Classification](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Classification.txt)

## Part 2. Data

- Chapter 4. [Working with numerical data](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Numerical%20data.txt)
- Chapter 5. [Working with categorical data](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Categorical%20data.txt)
- Chapter 6. [Datasets, generalization, and overfitting](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Datasets,%20generalization,%20and%20overfitting.txt)

## Part 3. Advanced ML models

- Chapter 7. [Neural networks](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Neural%20networks.txt)
- Chapter 8. [Embeddings](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Embeddings.txt)
- Chapter 9. [Large language models](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20LLM.txt)

## Part 4. Real-world ML

- Chapter 10. [Production ML systems](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Production%20ML%20systems.txt)
- Chapter 11. [Automated ML](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20AutoML.txt)
- Chapter 12. [Fairness](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Fairness.txt)