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

Name: Building Recommendation Systems in Python and Jax: Hands-On Production Systems at Scale
Brand: O'Reilly Media
SKU: 9781492097990
Price: 5483.0 INR
Availability: InStock

by Bryan Bischof

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ISBN13: 9781492097990
Binding: Paperback
Subject: N/A
Publisher: O'Reilly Media
Publisher Imprint: O'Reilly Media
Publication Date: January 30, 2024
Pages: 400
Original Price: GBP 63.99
Language: English
Edition: N/A
Item Weight: 563 grams
BISAC Subject(s): Data Science / Machine Learning, Logic Design, and Languages / Python

About The Book

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, Weights & Biases, and Kafka.

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

About The Author

Bischof, Bryan: - Dr. Bryan Bischof is the Head of Data Science at Weights and Biases, and an adjunct professor in the Rutgers Master of Business and Analytics program where he teaches Data Science. He has previously built recommendation systems for clothing (at Stitch Fix), and built the world's first recommendation system for coffee (at Blue Bottle Coffee). His research interests are in geometric methods for ML, including higher order graph methods and topological features. His data visualization work appeared in the popular book The Day it Finally Happens by Mike Pearl. His Ph.D. is in pure mathematics.

Yee, Hector: - Hector Yee is a Staff Software engineer at Google, where he has worked on multiple projects including creating the first content based ranker on Image Search, the self driving car perception, and writing the YouTube recommender system. He has won a technical Emmy for his work on personalized video ranking technology. He has an M.S. in computer graphics.

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