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

John Sukup

Get hands-on with the most widely used Python library in machine learning with over 80 practical recipes that cover core as well as advanced functions

Key Features

Solve complex business problems with data-driven approaches

Master tools associated with developing predictive and prescriptive models

Build robust ML pipelines for real-world applications, avoiding common pitfalls

Book Description

Trusted by data scientists, ML engineers, and software developers alike, scikit-learn offers a versatile, user-friendly framework for implementing a wide range of ML algorithms, enabling the efficient development and deployment of predictive models in real-world applications. This third edition of scikit-learn Cookbook will help you master ML with real-world examples and scikit-learn 1.5 features.

This updated edition takes you on a journey from understanding the fundamentals of ML and data preprocessing, through implementing advanced algorithms and techniques, to deploying and optimizing ML models in production. Along the way, you’ll explore practical, step-by-step recipes that cover everything from feature engineering and model selection to hyperparameter tuning and model evaluation, all using scikit-learn.

By the end of this book, you’ll have gained the knowledge and skills needed to confidently build, evaluate, and deploy sophisticated ML models using scikit-learn, ready to tackle a wide range of data-driven challenges.