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


You have now successfully trained all three types of AutoML models – classification, regression, and forecasting. Not only can you train a simple forecasting model, but you also know how to improve models with the various forecasting parameters and how to build high-performing baseline models with ARIMA and Prophet.

Moreover, you've acquired a lot of knowledge regarding how forecasting differs from other problems and how to avoid common pitfalls. By utilizing the forecast horizon feature wisely, you can forecast days, months or years into the future, and now it's time to add a powerful tool to your repertoire.

In Chapter 7, Using the Many Models Solution Accelerator, you will be able to build individual models for each time series grain. Instead of building one forecasting model, you can build thousands of models all at the same time and score them as if they were one model. You will find that this approach can vastly enhance your model's performance...