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Azure Machine Learning Studio for The Non-Data Scientist: Learn how to create experiments, operationalize them using Excel and Angular .Net Core ... programs to improve predictive results.

Azure Machine Learning Studio for The Non-Data Scientist: Learn how to create experiments, operationalize them using Excel and Angular .Net Core ... programs to improve predictive results.

Azure Machine Learning Studio for The Non-Data Scientist: Learn how to create
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Azure Machine Learning Studio for The Non-Data Scientist: Learn how to create experiments, operationalize them using Excel and Angular .Net Core ... programs to improve predictive results. Paperback - 2017

by Washington, Michael

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  • Title Azure Machine Learning Studio for The Non-Data Scientist: Learn how to create experiments, operationalize them using Excel and Angular .Net Core ... programs to improve predictive results.
  • Author Washington, Michael
  • Binding Paperback
  • Condition New
  • Pages 160
  • Volumes 1
  • Language ENG
  • Publisher Createspace Independent Publishing Platform
  • Publication date 2017-07-12
  • Bookseller's Inventory # 29878695-n
  • ISBN 9781548871123 / 1548871125
  • Weight 0.63 lbs (0.29 kg)
  • Dimensions 9.25 x 7.5 x 0.34 in (23.50 x 19.05 x 0.86 cm)
  • Category Computers - General Information
  • Quantity available 5

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Reader reviews for Azure Machine Learning Studio for The Non-Data Scientist: Learn how to create experiments, operationalize them using Excel and Angular .Net Core ... programs to improve predictive results.

From the publisher

Creating predictive models is no longer relegated to data scientists when you use tools such as the Microsoft Azure Machine Learning Studio. Azure Machine Learning Studio is a web browser-based application that allows you to create and deploy predictive models as web services that can be consumed by custom applications and other tools such as Microsoft Excel. With this book, you will learn how to create predictive experiments, operationalize them using Excel and Angular .Net Core applications, and create retraining programs to improve predictive results. Table of Contents Chapter 1: The Author is Not a Data Scientist * Why Do We Need Predictive Modeling? * An Introduction to Get You Started Chapter 2: An End-To-End Azure Machine Learning Studio Application * Create an Azure Machine Learning Workspace * Create An Experiment * Select Columns * Split Data * Train The Model * Score The Model * Evaluate The Model * Create A Predictive Web Service * Consume The Model Using Excel Chapter 3: An Angular 2 .Net Core Application Consuming an Azure Machine Learning Model * The Application * Creating The Application * Create The .Net Core Application * Add PrimeNG * Add The Database * Create Code To Call Azure Machine Learning Web Service * Create The Angular Application * Saving Data * Viewing Data Chapter 4: Retraining an Azure Machine Learning Application * The Retraining Process * Prepare The Training Data * Set-up An Azure Storage Account * Create The Batch Retraining Program * Get Required Values * Add A New Endpoint And Patch It * Consume The New Endpoint

About the author

Michael Washington is an ASP.NET, C#, and Visual Basic programmer. He has extensive knowledge in process improvement, billing systems, and student information systems. He is a Microsoft MVP. He has a son, Zachary, and resides in Los Angeles with his wife, Valerie.
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