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

Loading data into AMLS for AutoML

Just as you registered the Diabetes Open dataset in Chapter 2, Getting Started with Azure Machine Learning Service, you will now be registering a publicly available Titanic dataset using AMLS.

Unlike the diabetes dataset, however, you will load the data directly from your desktop to the portal. The Titanic dataset holds information relating to who survived and who died aboard the infamous ill-fated voyage. You will build a model that predicts survivors based on demographic information such as age and gender, as well as ticket information, such as passenger class and ticket price:

  1. First, you will need to download the Titanic data from the GitHub repository.
  2. Then, you will need to open up your Azure Machine Learning Studio by navigating to
  3. Once you are in the studio, click Datasets on the right-hand side of the studio under Assets.
  4. Then, click Create dataset and select From local files from the drop-down...