You're reading from Mastering Azure Machine Learning

Product typeBook

Published inApr 2020

Reading LevelBeginner

PublisherPackt

ISBN-139781789807554

Edition1st Edition

Languages

Tools

Azure

Concepts

Machine Learning

Authors (2):

Christoph Körner

Kaijisse Waaijer

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Collaborative filtering—a rating-based recommendation engine

By recommending only similar items or items from similar users, your users might get bored of the recommendations provided due to the lack of diversity and variety. Once a user starts interacting with a service, for example, watching videos on YouTube, reading and liking posts on Facebook, or rating movies on Netflix, we want to provide them with great personalized recommendations and relevant content to keep them happy and engaged. A great way to do so is to provide a good mix of similar content and new content to explore and discover.

Collaborative filtering is a popular approach for providing such diverse recommendations by comparing user-item interactions, finding other users who interact with similar items, and recommending items that those users also interacted with. It's almost as if you were to build many custom stereotypes and recommend other items consumed from the same stereotype. Figure 11.6 illustrates...

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Mastering Azure Machine Learning

Published in: Apr 2020Publisher: PacktISBN-13: 9781789807554

Authors (2)

Christoph Körner

Christoph Körner previously worked as a cloud solution architect for Microsoft, specializing in Azure-based big data and machine learning solutions, where he was responsible for designing end-to-end machine learning and data science platforms. He currently works for a large cloud provider on highly scalable distributed in-memory database services. Christoph has authored four books: Deep Learning in the Browser for Bleeding Edge Press, as well as Mastering Azure Machine Learning (first edition), Learning Responsive Data Visualization, and Data Visualization with D3 and AngularJS for Packt Publishing.
Read more about Christoph Körner

Kaijisse Waaijer

Kaijisse Waaijer is an experienced technologist specializing in data platforms, machine learning, and the Internet of Things. Kaijisse currently works for Microsoft EMEA as a data platform consultant specializing in data science, machine learning, and big data. She works constantly with customers across multiple industries as their trusted tech advisor, helping them optimize their organizational data to create better outcomes and business insights that drive value using Microsoft technologies. Her true passion lies within the trading systems automation and applying deep learning and neural networks to achieve advanced levels of prediction and automation.
Read more about Kaijisse Waaijer

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