Browse Library
Sign In Start Free Trial
Close icon Search icon
Account
Browse Library Advanced Search Sign In Start Free Trial

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Hands-On Machine Learning with Azure
  • Toc
  • feedback
Hands-On Machine Learning with Azure

Hands-On Machine Learning with Azure

By : Abraham, Parashar Shah, Jen Stirrup, Lauri Lehman, Anindita Basak, Murphy
2.7 (3)
close
Hands-On Machine Learning with Azure

Hands-On Machine Learning with Azure

2.7 (3)
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)
close
close
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
AI Cloud Foundations
AI Cloud Foundations
The importance of artificial intelligence
The emergence of the cloud
The Microsoft cloud – Azure
Summary
2
Data Science Process
Data Science Process
TDSP stages
Tools for TDSP
Summary
3
Cognitive Services
Cognitive Services
Cognitive Services for Vision APIs
The Computer Vision API
Face API
Cognitive Services for Language APIs
Cognitive Services for Speech APIs
Cognitive Services for Knowledge APIs
Cognitive Services for Search APIs
Summary
Reference
4
Bot Framework
Bot Framework
What is a bot?
Creating a bot with Bot Service
Summary
5
Azure Machine Learning Studio
Azure Machine Learning Studio
Deploying an Azure AI Gallery template
Building an experiment
Deploying a model as a web service
Summary
6
Scalable Computing for Data Science
Scalable Computing for Data Science
Different scalable compute options in Azure
Introduction to DSVMs
DLVM
Batch AI service
ACI
AKS
Summary
7
Machine Learning Server
Machine Learning Server
What is Microsoft ML Server?
Machine learning with Python
Summary
8
HDInsight
HDInsight
R with HDInsight
Getting started with Azure HDInsight and ML services
HDInsight and data analytics with R
Enriching data for analysis
Summary
9
Machine Learning with Spark
Machine Learning with Spark
Machine learning with Azure Databricks
Getting started with Apache Spark and Azure Databricks
Using SQL in Azure Databricks
Machine Learning with HDInsight
HDInsight and Spark
Working with data in a Spark environment
Configuring the data science virtual machine
Setting up an HDInsight cluster with Spark
Summary
Further references
10
Building Deep Learning Solutions
Building Deep Learning Solutions
What is deep learning?
Overview of the Azure Notebook service
Overview of Azure Deep Learning Virtual Machine toolkits
An overview of the Microsoft Machine Learning Library for Apache Spark (MMLSpark)
Overview of TensorFlow on Azure
Summary
11
Integration with Other Azure Services
Integration with Other Azure Services
Logic Apps
Azure Functions
Azure Data Lake Analytics
Azure Data Factory
Summary
12
End-to-End Machine Learning
End-to-End Machine Learning
Using the Azure Machine Learning SDK for E2E machine learning
Summary
13
Other Books You May Enjoy
chevron up
Other Books You May Enjoy
Leave a review - let other readers know what you think

Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Stream Analytics with Microsoft Azure
Anindita Basak

ISBN: 9781788395908

  • Perform real-time event processing with Azure Stream Analysis
  • Incorporate the features of Big Data Lambda architecture pattern in real-time data processing
  • Design a streaming pipeline for storage and batch analysis
  • Implement data transformation and computation activities over stream of events
  • Automate your streaming pipeline using Powershell and the .NET SDK
  • Integrate your streaming pipeline with popular Machine Learning and Predictive Analytics modelling algorithms
  • Monitor and troubleshoot your Azure Streaming jobs effectively

Hands-On Data Warehousing with Azure Data Factory
Christian Cote

ISBN: 9781789137620

  • Understand the key components of an ETL solution using Azure Data Factory and Integration...
End of Section 1
Next Section
bookmark search playlist download
font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected
Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete