Models Demystified

I have a book coming out! Models are everywhere, from the weather forecast to the stock market, they can help us make sense of the world and make better decisions. But they can also be confusing and intimidating, and the modeling world tough to navigate. Along with my co-author Seth Berry, our goal with the book is to equip you with a better understanding of how models work and how to use them, including both basic and more advanced techniques, where we attempt to demystify models in data science from linear regression to deep learning. It’s a practical guide to help you understand the models that power the world around you.

While not quite to the finish line, most of the book is written and in the editing stage as of February. It will be published sometime in 2025 on CRC Press as part of the Data Science Series. In the meantime, you can access the book here, and it will continue to be developed as time goes on.

Models Demystified Table of Contents:

1. Introduction
2. Thinking About Models
3. The Foundation
4. Understanding the Model
5. Understanding the Features
6. Model Estimation and Optimization
7. Estimating Uncertainty
8. Generalized Linear Models
9. Extending the Linear Model
10. Core Concepts in Machine Learning
11. Common Models in Machine Learning
12. Extending Machine Learning
13. Causal Modeling
14. Dealing with Data
15. Danger Zone
16. Parting Thoughts

All examples are in Python and R, and with separate notebooks you can use yourself for more exploration.

We welcome any feedback in the meantime as it continues to develop, so please feel free to create an issue. For contributions, please see the contributing page for more information. Thanks for reading, and hope you enjoy it!