Book Image

Hands-On Machine Learning with Azure

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

Hands-On Machine Learning with Azure

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

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)

Machine learning with Azure Databricks

By adopting ML, enterprises are looking to improve their business, or even radically transform it by using data as the lifeblood for digital transformation. Databricks empowers companies to develop their data science competency quickly, and turn that into a competitive advantage by providing a fully integrated unified analytics platform in Azure.

Enterprises want to leverage the treasure trove of data they have collected historically. Organizations have begun to collect more data recently. This includes data in a variety of forms, including new customer data in the form of clickstreams, web logs, and sensor data from Internet of Things devices and machines, as well as audio, images, and videos.

Using insights from this data, enterprises across various verticals can improve business outcomes in many different ways that impact our daily lives...