Pdf Book Name: Practical Recommender Systems
Author: Kim Falk
Publisher: Manning Publications
File size: 14.8 MB
File format: PDF
Practical Recommender Systems Pdf Book Description:
Practical Recommender Systems is primarily intended for developers who are interested in implementing a recommender. The book takes a practical approach and attempts to explain everything in normal, everyday language. There will be math and statistics, but both will be accompanied by figures and code. New data scientists will also benefit from this book as an introduction to recommender algorithms and to the infrastructure needed to get them up and running. Managers will find this book useful to get an overview of what a recommender system is and how it can be used in practice. To get the full value out of the book, you should be able to read code in a programming language such as Python or Java, you should understand an SQL query, and you should have a basic understanding of higher math and statistics. Figures and code listings that explain concepts can get you only so far.I want to mention and acknowledge two groups of people here: those who actively worked on the book and those who suffered and supported my constantly distracted presence for the last three years while this book project has been under way. It might be my name on the cover of Practical Recommender Systems, but this book couldn’t have come into existence without the great work of the people at Manning. I want especially to thank Helen Stergius for her relentless help and guidance as my development editor. She and all the others have translated my slightly dyslexic writing into something that teaches people to implement recommenders.
Recommender systems are almost a requirement for maintaining a website’s content current, helpful, and interesting for people. Recommender systems are everywhere, assisting you to find everything from films to tasks, restaurants to hospitals, and even love. Practical Recommender Systems goes behind the curtain to show readers the way recommender systems operate and, furthermore, the way to produce and apply them to get their website. This hands on manual covers scaling issues and other problems they might encounter as their website develops.The goal of the book is to introduce you to recommender systems—not only the algorithms, but also the recommender system ecosystem. The algorithms aren’t too complex, but to understand and run them requires understanding the users who are to receive the recommendations. The book’s contents have evolved during writing, because I’ve tried to fit more and more in. I hope reading this book will provide everything you need to know to get started on recommenders and give you a solid foundation to build on as you learn more.
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