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Scikit-learn Cookbook

You're reading from Scikit-learn Cookbook Over 80 recipes for machine learning in Python with scikit-learn

Product type Paperback

Published in Dec 2025

Last Updated in Sep 2025

Publisher Packt

ISBN-13 9781836644453

Length 414 pages

Edition 3rd Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Author (1):

John Sukup

View More author details

Table of Contents (14) Chapters

1. Scikit-learn Cookbook, Third Edition: Over 80 recipes for machine learning in Python with scikit-learn

2. Chapter 1: Common Conventions and API Elements of scikit-learn FREE CHAPTER

3. Chapter 2: Pre-Model Workflow and Data Preprocessing

4. Chapter 3: Dimensionality Reduction Techniques

5. Chapter 4: Building Models with Distance Metrics and Nearest Neighbors

6. Chapter 5: Linear Models and Regularization

7. Chapter 6: Advanced Logistic Regression and Extensions

8. Chapter 7: Support Vector Machines and Kernel Methods

9. Chapter 8: Tree-Based Algorithms and Ensemble Methods

10. Chapter 9: Text Processing and Multiclass Classification

11. Chapter 10: Clustering Techniques

12. Chapter 11: Novelty and Outlier Detection

13. Chapter 12: Cross-Validation and Model Evaluation Techniques

14. Chapter 13: Deploying scikit-learn Models in Production

Technical requirements

It is advisable to create a Python environment for safely isolating your work from other Python installations/libraries. See the GitHub Repo for more details (https://github.com/PacktPublishing/Scikit-Learn-Cookbook-Third-Edition).

Git 2.46.x

Python 3.9.x

Cloned GitHub Repo and Python environment built from requirements.txt file

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Programming languages

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Authors (1)

John Sukup

John Sukup

John Sukup is a seventeen-year data professional. His experience working with data spans from consumer market research to data science to ML and AI. He has over a decade of experience as an AI/ML cloud engineer and consultant at multiple international organizations including Levi Strauss, Cisco, Anaconda, and Ipsos. He has acted as the lead professional trainer for Fortune 100 organizations and has been featured in Forbes, Oracle, and Data Science Central. He currently acts as Managing Director and Founder at Expected X, an AI Solution Design and Consultancy as well as cohost of the Unriveted Podcast with his colleague Martin Miller.

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