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

Welcome to Packt Early Access. We’re giving you an exclusive preview of this book before it goes on sale. It can take many months to write a book, but our authors have cutting-edge information to share with you today. Early Access gives you an insight into the latest developments by making chapter drafts available. The chapters may be a little rough around the edges right now, but our authors will update them over time.

You can dip in and out of this book or follow along from start to finish; Early Access is designed to be flexible. We hope you enjoy getting to know more about the process of writing a Packt book.

1. Chapter 1: Common Conventions and API Elements of Scikit-Learn
2. Chapter 2: Pre-Model Workflow and Data Preprocessing
3. Chapter 3: Dimensionality Reduction Techniques
4. Chapter 4: Building Models with Distance Metrics and Nearest Neighbors
5. Chapter 5: Linear Models and Regularization
6. Chapter 6: Advanced Logistic Regression and Extensions
7. Chapter 7: Support Vector Machines and Kernel Methods
8. Chapter 8: Tree-Based Algorithms and Ensemble Methods
9. Chapter 9: Text Processing and Multiclass Classification
10. Chapter 10: Clustering Techniques
11. Chapter 11: Novelty and Outlier Detection
12. Chapter 12: Cross-Validation and Model Evaluation Techniques
13. Chapter 13: Deploying Scikit-Learn Models in Production