Building recommendation systems in python and jax: hands-on production systems at...
Описание
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
Також купити книгу Building Recommendation Systems in Python and JAX: Hands-On
Production Systems at Scale, Bryan Bischof Ph.D, Hector Yee Ви можете по
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