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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.
However, the author is not a data scientist. Therefore, you do not need to be a data scientist to use this book. You do not even need to be a computer programmer; however, if you are, it will help you understand the chapters that cover how to operationalize the sample predictive model, by creating an Angular application, and to retrain that model using C# code.
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