Building Recommendation Systems in Python and JAX

eBook Details:

• Paperback: 400 pages
• Publisher: WOW! eBook (January 30, 2024)
• Language: English
• ISBN-10: 1492097993
• ISBN-13: 978-1492097990

eBook Description:

Building Recommendation Systems in Python and JAX: Hands-On Production Systems at Scale

Implementing and designing systems that make suggestions to users are among the most popular and essential machine learning applications available. Whether you want customers to find the most appealing items at your online store, videos to enrich and entertain them, or news they need to know, recommendation systems (RecSys) provide the way.

You’ll learn:

• The data essential for building a RecSys
• How to frame your data and business as a RecSys problem
• Ways to evaluate models appropriate for your system
• Methods to implement, train, test, and deploy the model you choose
• Metrics you need to track to ensure your system is working as planned
• How to improve your system as you learn more about your users, products, and business case

In this Building Recommendation Systems in Python and JAX practical book, authors Bryan Bischof and Hector Yee illustrate the core concepts and examples to help you create a RecSys for any industry or scale. You’ll learn the math, ideas, and implementation details you need to succeed. This book includes the RecSys platform components, relevant MLOps tools in your stack, plus code examples and helpful suggestions in PySpark, SparkSQL, FastAPI, Weights & Biases, and Kafka.