Book Image

Automated Machine Learning with Microsoft Azure

By : Dennis Michael Sawyers
Book Image

Automated Machine Learning with Microsoft Azure

By: Dennis Michael 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)
Section 1: AutoML Explained – Why, What, and How
Section 2: AutoML for Regression, Classification, and Forecasting – A Step-by-Step Guide
Section 3: AutoML in Production – Automating Real-Time and Batch Scoring Solutions

Chapter 2: Getting Started with Azure Machine Learning Service

Now that we know that the key to delivering return on investment in artificial intelligence is delivering machine learning (ML) projects at a brisk pace, we need to learn how to use Automated Machine Learning (AutoML) to achieve that goal. Before we can do that, however, we need to learn how to use the Azure Machine Learning Service (AMLS). AMLS is Microsoft's premier ML platform on the Azure cloud.

We will begin this chapter by creating an Azure account and creating an AMLS workspace. Once you have created a workspace, you will proceed to create different types of compute to run Python code and ML jobs remotely using a cluster of machines. Next, you will learn how to work with data using the Azure dataset and datastore constructs. Finally, we will provide an overview of AutoML. This will boost your ability to create high-performing models.

In this chapter, we will cover the following topics:

  • Creating...