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

Interpreting your AutoML results

Your training run should have taken about 15 minutes and produced a model with around 80% accuracy. However, there is much more to your results than this simple metric. There are data guardrails that will inform you of any problems with your data. There is also a slew of different metrics for each of the three problem types and accompanying charts and graphs that can assist you in presenting your results to the business:

  1. To begin, click Automated ML from the left-hand menu of AMLS and click the latest run from your Titanic-Training experiment, as seen in Figure 3.12:

    Figure 3.12 – Examining your results

    You will be taken to a screen with a variety of metrics regarding your model, including the type of algorithm used to train the best-performing model, its accuracy score, the date and time it was created, and how long your AutoML run took to execute. Take advantage of the Description area in the bottom-right corner of your screen to write...