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)

End-to-End Machine Learning

In this chapter, we will learn about the new capabilities that were launched with the Azure Machine Learning service that can help data scientists and AI developers with end-to-end (E2E) machine learning.

When developing AI applications, we can use cognitive services, as described in Chapter 3, Cognitive Services. Alternatively, we can create custom machine learning models with our own data, because cognitive services won't work in every possible scenario. In cases such as these, we have to train our own machine learning algorithms. The Azure Machine Learning service has an SDK, CLI, and APIs that can help you to create these custom models.

In this chapter, we are going to learn how to use the Azure Machine Learning SDK for Python in order to carry out E2E machine learning.