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)

Batch AI service

DSVMs and DLVMs are good at carrying out single node-based computing. In scenarios where we need to distribute training, however, we can use the Batch AI service, which allows us to focus on training instead of having to worry about managing the cluster. A Batch AI service has VMs that use the same base image as the DSVM, meaning that all the libraries, tools, and frameworks that are available in a DSVM are available in the Batch AI service as well. The Batch AI service allows us to use parallel training and GPU-based VMs for deep learning, and we can also deploy a Docker container to a Batch AI node. When using the Batch AI service, we can mount our Azure Blob or Azure Data Lake Storage with our cluster. This means that we can train with a huge amount of data without having to copy the data to the cluster because it can be streamed instead.

At the time of writing...