About This Book
Background
1. Information Theory
2. Cross Validation
3. Evaluating Predictive Distributions
4. Optimization for Machine Learning
Neural Networks
5. Feed-Forward Neural Networks
6. Recurrent Neural Networks
7. LSTM Networks
8. Empirical Exercise: Networks for Time Series
9. Distribution Modeling with Neural Networks
Tree-Based Methods
10. Decision Trees
11. Random Forests
12. Gradient Boosting
13. Advanced Tree-Based Methods
Further Topics
14. Advanced Hyperparameter Optimization
15. Conformal Prediction
16. Foundation Models for Economic Text
17. Data Sets Used in This Book
On this page
References
Under active development.
A stable version is expected in November 2026. Feedback is very welcome.
References