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Introduction to Azure Machine Learning Workbench

Contents

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Introduction
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Introduction2m
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Overview2m 1s
Using Azure ML Workbench
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Installation3m 6s
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Basic Data Preparation8m 22s
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Training a Model12m 40s
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Deploying a Model13m 2s
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Advanced Data Preparation23m 40s
Conclusion
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Conclusion2m 20s
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Overview
Transcript
DifficultyIntermediate
Duration1h 7m 11s

Description

Course Description

Azure Machine Learning Workbench is a front-end for a variety of tools and services, including the Azure Machine Learning Experimentation and Model Management services.

Workbench is a relatively open toolkit. First, you can use almost any Python-based machine learning framework, such as Tensorflow or scikit-learn. Second, you can train and deploy your models either on-premises or on Azure.

Workbench also includes a great data-preparation module. It has a drag-and-drop interface that makes it easy to use, but its features are surprisingly sophisticated.

In this course, you will learn how Workbench interacts with the Experimentation and Model Management services, and then you will follow hands-on examples of preparing data, training a model, and deploying a trained model as a predictive web service.

Learning Objectives

  • Prepare data for use by an Azure Machine Learning Workbench experiment.
  • Train a machine learning model using Azure Machine Learning Workbench.
  • Deploy a model trained in Azure Machine Learning Workbench to make predictions.

Intended Audience

  • Anyone interested in Azure’s machine learning services

Prerequisites

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Resources

The github repository for this course can be found here.  

About the Author

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Guy launched his first training website in 1995 and he's been helping people learn IT technologies ever since. He has been a sysadmin, instructor, sales engineer, IT manager, and entrepreneur. In his most recent venture, he founded and led a cloud-based training infrastructure company that provided virtual labs for some of the largest software vendors in the world. Guy’s passion is making complex technology easy to understand. His activities outside of work have included riding an elephant and skydiving (although not at the same time).

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