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 10: Creating End-to-End AutoML Solutions

Now that you have created machine learning (ML) pipelines, you can learn how to use them in other Azure products outside of the Azure Machine Learning Service (AMLS). Perhaps the most useful is Azure Data Factory.

Azure Data Factory (ADF) is Azure's premier code-free data orchestration tool. You can use ADF to pull data from on-premise sources into the Azure cloud, to run ML pipelines, and push data out of Azure by creating an Azure Data Factory pipeline (ADF pipeline). ADF pipelines are an integral part of creating end-to-end ML solutions and are the end goal of any non-real-time AutoML project.

You will begin this chapter by learning how to connect AMLS to ADF. Once you have accomplished this task, you will learn how to schedule an ML pipeline using the parallel pipeline you created in Chapter 9, Implementing a Batch Scoring Solution.

Next, you will learn how to pull data from your local machine and load it into the...