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

Transferring data using ADF

Moving data from on-premise to the cloud and from the cloud to on-premise is a key skill for any data engineer or data scientist. ADF accomplishes this task with the Copy data activity. This is ADF's most basic and most powerful function.

In this section, first, you will download a self-hosted integration runtime (SHIR) to your local machine, allowing your computer to serve as a compute resource to load data into Azure. Then, you will create a linked service for your Azure storage account and your local PC.

Next, you will download a file from the GitHub repository and save it to your PC. Finally, you will create a Copy data activity in ADF that will take data from your PC and put it into the same Azure blob container that's connected to your AML datastore.

Going through these exercises will give you the data engineering skills that will allow you to create an end-to-end solution in the next section.

Installing a self-hosted integration...