Authors:
- Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models.
- The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models.
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Table of contents (14 chapters)
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Front Matter
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Introducing Data Science and Microsoft Azure Machine Learning
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Front Matter
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Statistical and Machine Learning Algorithms
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Front Matter
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Back Matter
About this book
Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models.
The authors use task oriented descriptions and concrete end-to-end examples to ensure that the reader can immediately begin using this new service. The book describes all aspects of the service from data ingress to applying machine learning, evaluating the models, and deploying them as web services.
Learn how you can quickly build and deploy sophisticated predictive models with the new Azure Machine Learning from Microsoft.
What’s New in the Second Edition?
Five new chapters have been added with practical detailed coverage of:
- Python Integration – a new feature announced February 2015
- Data preparation and feature selection
- Data visualization with Power BI
- Recommendation engines
- Selling your models on Azure Marketplace
About the authors
Bibliographic Information
Book Title: Predictive Analytics with Microsoft Azure Machine Learning 2nd Edition
Authors: Roger Barga, Valentine Fontama, Wee Hyong Tok
DOI: https://doi.org/10.1007/978-1-4842-1200-4
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Valentine Fontama and Roger Barga and Wee Hyong Tok 2015
Softcover ISBN: 978-1-4842-1201-1Published: 19 August 2015
eBook ISBN: 978-1-4842-1200-4Published: 26 August 2015
Edition Number: 2
Number of Pages: XXIII, 291
Number of Illustrations: 227 b/w illustrations
Topics: Artificial Intelligence, Software Engineering/Programming and Operating Systems, Data Mining and Knowledge Discovery