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)

Overview of TensorFlow on Azure

TensorFlow is an open source, deep learning library that was introduced by Google and is used for solving a range of tasks. TensorFlow was introduced to fulfill the requirement of building and training complex neural networks in order to detect and decipher patterns, recognitions, and correlations, similar to that of the learning process of the human brain. Google introduced the TPU (Tensor Processing Unit) cloud platform for running the TensorFlow Python API and utilizing TensorFlow graph units.

In order to get started on TensorFlow with Azure, the two easiest options are as follows:

  • Using Deep Learning toolkit for Data Science VM (Deep Learning VM): Provides a Windows GPU version of mxnet, CNTK, TensorFlow, and Keras that's able to run on a GPU-NC, N-series, or FPGA infrastructure.
  • Using Data Science VM for Azure: Support for CNTK, TensorFlow...