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Building Recommendation Systems in Python and Jax - Hands-On Production Systems at Scale
Loot Price: R1,323
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Building Recommendation Systems in Python and Jax - Hands-On Production Systems at Scale
Expected to ship within 12 - 17 working days
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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, 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
General
Imprint: |
O'Reilly Media
|
Country of origin: |
United States |
Release date: |
2024 |
Authors: |
Bryan Bischof
• Hector Yee
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Dimensions: |
233 x 178mm (L x W) |
Pages: |
400 |
ISBN-13: |
978-1-4920-9799-0 |
Categories: |
Books
Promotions
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LSN: |
1-4920-9799-3 |
Barcode: |
9781492097990 |
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