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Microsoft Azure Machine Learning

You're reading from  Microsoft Azure Machine Learning

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781784390792
Pages 212 pages
Edition 1st Edition
Languages
Authors (2):
Sumit Mund Sumit Mund
Profile icon Sumit Mund
Christina Storm Christina Storm
Profile icon Christina Storm
View More author details
Toc

Table of Contents (21) Chapters close

Microsoft Azure Machine Learning
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Introduction ML Studio Inside Out Data Exploration and Visualization Getting Data in and out of ML Studio Data Preparation Regression Models Classification Models Clustering A Recommender System Extensibility with R and Python Publishing a Model as a Web Service Case Study Exercise I Case Study Exercise II Index

Chapter 9. A Recommender System

Recommender systems are common these days. You may not have noticed, but you might already be a user or receiver of such a system somewhere. Most of the well-performing e-commerce platforms use recommendation systems to recommend items to their users. When you see on the Amazon website that a book is recommended to you based on your earlier preferences, purchases, and browse history, Amazon is actually using such a recommendation system. Similarly, Netflix uses its recommendation system to suggest movies for you.

A recommender or recommendation system is used to recommend a product or information often based on user characteristics, preferences, history, and so on. So, a recommendation is always personalized.

Until recently, it was not so easy or straightforward to build a recommender, but Azure ML makes it really easy to build one as long as you have your data ready.

This chapter introduces you to the concept of recommendation systems and also the model available...

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