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

Connecting AMLS to ADF

ADF is a code-free data orchestration and transformation tool. With it, you can create ADF pipelines that can copy data into Azure, transform data, run ML pipelines, and push data back onto certain on-premise databases and file shares. It's incredibly easy to make and schedule ADF pipelines using ADF's code-free pipeline editing tool. As you create an ADF pipeline with the drag and drop interface, you're actually writing JSON code, which ADF uses to execute jobs.


Azure Synapse Analytics, Microsoft Azure's premier data warehousing and integrated analytics service, also has a feature nearly identical to ADF pipelines: Azure Synapse pipelines. Anything that you do in this chapter with ADF pipelines you can also achieve with Azure Synapse pipelines using a very similar interface.

In this section, you will create an ADF resource and connect it to AMLS. You will do this using a linked service, an object similar to a connection string...