Building Recommendation Systems in Python and JAX eBook

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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 (RecSys) provide the way. In this 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, and Weights & Biases. 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

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Additional ISBNs
9781492097969

Building Recommendation Systems in Python and JAX 1st Edition is written by Bryan Bischof Ph.D; Hector Yee and published by O’Reilly Media. The Digital and eTextbook ISBNs for Building Recommendation Systems in Python and JAX are 9781492097952, 1492097950 and the print ISBNs are 9781492097990, 1492097993. Additional ISBNs for this eTextbook include 9781492097969.