Building Recommendation Systems in Python and JAX
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Building Recommendation Systems in Python and JAX
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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 (Rec Sys) provide the way. In this practical book, authors Bryan Bischof and Hector Yee illustrate the core concepts and examples to help you create a Rec Sys for any industry or scale. You'll learn the math, ideas, and implementation details you need to succeed.
This book includes the Rec Sys platform components, relevant MLOps tools in your stack, plus code examples and helpful suggestions in Py Spark, Spark SQL, Fast API, and Weights & Biases. You'll learn: The data essential for building a Rec Sys How to frame your data and business as a Rec Sys 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
Book Details
- Authors: Bryan Bischof Ph.D, Hector Yee
- Publisher: O'Reilly Media
- eBook ISBN: 9781492097952, 1492097950
- Print ISBN: 9781492097990, 1492097993
- Other ISBNs: 9781492097969
