Recommendation systems (RecSys) are popular machine learning applications that make suggestions to users. This practical book by Bryan Bischof and Hector Yee illustrates the core concepts and examples to help you create a RecSys for any industry or scale, including the RecSys platform components, relevant MLOps tools, code examples, and suggestions in PySpark, SparkSQL, FastAPI, Weights & Biases, and Kafka.

Format: Paperback / softback
Length: 400 pages
Publication date: 19 December 2023
Publisher: O'Reilly Media

Implementing and Designing Recommendation Systems: A Practical Guide

Recommendation systems (RecSys) have become increasingly popular and essential in various machine learning applications, enabling users to discover the most appealing items, videos, or news tailored to their preferences. In this comprehensive book, authors Bryan Bischof and Hector Yee provide a hands-on guide to creating RecSys for any industry or scale.

The book begins by introducing the core concepts and principles of RecSys, including data representation, model training, evaluation, and deployment. It explains the importance of understanding the data and business aspects as RecSys problems and outlines various ways to frame and evaluate models. The authors then delve into the implementation details, covering popular frameworks such as PySpark, SparkSQL, FastAPI, Weights & Biases, and Kafka.

Throughout the book, practical code examples and helpful suggestions are provided, allowing readers to apply the learned concepts to their own projects. The RecSys platform components are extensively discussed, along with relevant MLOps tools that can be integrated into your stack. Readers will gain a deep understanding of the data requirements for building a RecSys, how to frame their data and business as RecSys problems, and effective methods to implement, train, test, and deploy the model of their choice.

Key metrics to track and evaluate the performance of the RecSys system are also covered, ensuring that it is working as intended. The book emphasizes the importance of continuous improvement by learning more about users, products, and business cases. By applying the principles and techniques outlined in this book, readers will be well-equipped to build robust and effective RecSys systems that enhance user experiences and drive business growth.

Whether you are a data scientist, engineer, or business professional interested in leveraging recommendation systems, this practical guide is a valuable resource for advancing your knowledge and skills in this field.

Weight: 618g
Dimension: 178 x 233 x 21 (mm)
ISBN-13: 9781492097990