The Orange Book of Machine Learning - Green edition
The Orange Book of Machine Learning - Green edition
The essentials of making predictions using supervised regression and classification for tabular data.
About the Book
This 'Green' edition is actively maintained and will be subject to updates. Purchasers have permanent access to the very latest version and (should) be notified by email when an updated version for download is available.
The book covers the following topics in the context of supervised learning for tabular data:
1. Introduction
2. Statistics
3. Exploratory data analysis (EDA)
4. Data cleaning
5. Cross-validation
6. Interpolation and smoothing
7. Regression
8. Classification
9. Ensemble estimators
10. Hyperparameter optimization (HPO)
11. Feature engineering and selection
12. Why no neural networks/deep learning?
About the Author
Reader Testimonials
Valeriy Manokhin, PhD, MBA, CQF
Experienced Data Science Leader
Tabular data remains the backbone of any company, and it's refreshing to see a modern take on the subject in 2025 that focuses on what truly matters.
Venkat Sai Suman
PhD Candidate
The original edition is the goat book that still makes my life easy as a researcher in the intersection of AI/ML, network sciences and large dataset analysis.
Igor Shuryak, MD, PhD
Columbia University Professor / Quantitative Radiation Biologist/Oncologist
Orange book... ...is a great source of advice and useful information for analyzing tabular data, which is what I work with most of the time!
Jack Rodenberg
Machine Learning and Data Science Consultant
The "Green Book" is a fantastic resource for all Data Scientists, I would say it should be on every DS desk, but given it's an e-book that will be updated continually, you should purchase it, bookmark it on your browser and refer to it often.
Nikos Kafritsas
Data Scientist
...your book helped me grasp the whole concept of conformal prediction in just 10 minutes - even though I had come across numerous online posts and articles, none of them presented the full picture as clearly and concisely as you did.
Table of Contents
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