Predictive Analytics with Microsoft Azure Machine Learning, 2nd Edition Front Cover

Predictive Analytics with Microsoft Azure Machine Learning, 2nd Edition

  • Length: 291 pages
  • Edition: 2nd ed. 2015
  • Publisher:
  • Publication Date: 2015-08-19
  • ISBN-10: 1484212010
  • ISBN-13: 9781484212011
  • Sales Rank: #618247 (See Top 100 Books)
Description

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

Table of Contents

Part I: Introducing Data Science and Microsoft Azure Machine Learning
Chapter 1: Introduction to Data Science
Chapter 2: Introducing Microsoft Azure Machine Learning
Chapter 3: Data Preparation
Chapter 4: Integration with R
Chapter 5: Integration with Python

Part II: Statistical and Machine Learning Algorithms
Chapter 6: Introduction to Statistical and Machine Learning Algorithms

Part III: Practical Applications
Chapter 7: Building Customer Propensity Models
Chapter 8: Visualizing Your Models with Power BI
Chapter 9: Building Churn Models
Chapter 10: Customer Segmentation Models
Chapter 11: Building Predictive Maintenance Models
Chapter 12: Recommendation Systems
Chapter 13: Consuming and Publishing Models on Azure Marketplace
Chapter 14: Cortana Analytics

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