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  • Book Overview & Buying Automated Machine Learning with Microsoft Azure
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Automated Machine Learning with Microsoft Azure

Automated Machine Learning with Microsoft Azure

By : Dennis Michael Sawyers , Dennis Sawyers
4.9 (18)
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Automated Machine Learning with Microsoft Azure

Automated Machine Learning with Microsoft Azure

4.9 (18)
By: Dennis Michael Sawyers , Dennis Sawyers

Overview of this book

Automated Machine Learning with Microsoft Azure will teach you how to build high-performing, accurate machine learning models in record time. It will equip you with the knowledge and skills to easily harness the power of artificial intelligence and increase the productivity and profitability of your business. Guided user interfaces (GUIs) enable both novices and seasoned data scientists to easily train and deploy machine learning solutions to production. Using a careful, step-by-step approach, this book will teach you how to use Azure AutoML with a GUI as well as the AzureML Python software development kit (SDK). First, you'll learn how to prepare data, train models, and register them to your Azure Machine Learning workspace. You'll then discover how to take those models and use them to create both automated batch solutions using machine learning pipelines and real-time scoring solutions using Azure Kubernetes Service (AKS). Finally, you will be able to use AutoML on your own data to not only train regression, classification, and forecasting models but also use them to solve a wide variety of business problems. By the end of this Azure book, you'll be able to show your business partners exactly how your ML models are making predictions through automatically generated charts and graphs, earning their trust and respect.
Table of Contents (17 chapters)
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1
Section 1: AutoML Explained – Why, What, and How
5
Section 2: AutoML for Regression, Classification, and Forecasting – A Step-by-Step Guide
10
Section 3: AutoML in Production – Automating Real-Time and Batch Scoring Solutions

Chapter 3: Training Your First AutoML Model

With an Azure account, an Azure Machine Learning workspace, a compute cluster, and a basic understanding of how AutoML works, you're now ready to train your first automated machine learning model. It will be easy and straightforward: AutoML is an equalizer that enables even novices to create advanced models in mere minutes, and you will appreciate its power by the end of this chapter regardless of your background. Practice makes perfect, and this chapter is your first step toward becoming an AutoML practitioner.

You will begin this chapter by loading data from your local machine to your Azure Machine Learning Studio (AML Studio), selecting only the columns you need for training. Then, you will proceed to train an AutoML model using the guided user interface. After training your model, you will learn how to interpret your results directly from the AMLS portal. This includes not only standard metrics such as accuracy, false positive...

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