Book Image

Hands-On Machine Learning with Azure

By : Abraham, Parashar Shah, Jen Stirrup, Lauri Lehman, Anindita Basak, Murphy
Book Image

Hands-On Machine Learning with Azure

By: Abraham, Parashar Shah, Jen Stirrup, Lauri Lehman, Anindita Basak, Murphy

Overview of this book

Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML projects in the cloud in a cost-effective way. The book begins by covering the benefits of ML and AI in the cloud. You will then explore Microsoft’s Team Data Science Process to establish a repeatable process for successful AI development and implementation. You will also gain an understanding of AI technologies available in Azure and the Cognitive Services APIs to integrate them into bot applications. This book lets you explore prebuilt templates with Azure Machine Learning Studio and build a model using canned algorithms that can be deployed as web services. The book then takes you through a preconfigured series of virtual machines in Azure targeted at AI development scenarios. You will get to grips with the ML Server and its capabilities in SQL and HDInsight. In the concluding chapters, you’ll integrate patterns with other non-AI services in Azure. By the end of this book, you will be fully equipped to implement smart cognitive actions in your models.
Table of Contents (14 chapters)

Deploying an Azure AI Gallery template

Developing models with ML Studio does not have to be done from scratch. Azure AI Gallery contains a wide selection of templates for many different scenarios. These scenarios include many common use cases for ML, such as credit risk prediction, demand estimation, and text sentiment analysis. Templates can be imported to an Azure ML Studio Workspace with a few clicks and they contain all the steps needed to produce a working ML model. Studying templates is a great way to learn about different use cases and the steps required to produce an ML model. Some templates are prepared by Microsoft, but users can also submit their own experiments to the gallery.

The template gallery can be accessed directly from ML Studio. Open the ML Studio UI (as described previously) and create a new experiment by clicking on the + New in the bottom-left corner. This...