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You're reading from Hands-On Machine Learning with Azure Build powerful models with cognitive machine learning and artificial intelligence

Product type Paperback

Published in Oct 2018

Publisher Packt

ISBN-13 9781789131956

Length 340 pages

Edition 1st Edition

Languages

Python

Tools

Azure

Concepts

Artificial Intelligence

Authors (6):

Jen Stirrup

Ryan Murphy

Anindita Basak

Thomas K Abraham

Parashar Shah

Lauri Lehman

+2 more

View More author details

Table of Contents (14) Chapters

Preface

1. AI Cloud Foundations FREE CHAPTER

2. Data Science Process

3. Cognitive Services

4. Bot Framework

5. Azure Machine Learning Studio

6. Scalable Computing for Data Science

7. Machine Learning Server

8. HDInsight

9. Machine Learning with Spark

10. Building Deep Learning Solutions

11. Integration with Other Azure Services

12. End-to-End Machine Learning

13. Other Books You May Enjoy

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HDInsight and data analytics with R

Firstly, we need to get our data into Azure so that HDInsight can see it. We can upload data directly to Azure Storage, or we can use functionality in SQL Server Integration Services (SSIS). SSIS has the capability of connecting to Azure Blob Storage and Azure HDInsight. It enables you to create integration service packages that transfer data between an Azure Blob Storage and the on-premise data source. Then, the Azure HDInsight process can conduct processing on the data.

In order to get the data into HDInsight using SSIS, it's necessary to install the Azure Feature Pack. The Microsoft SSIS Feature Pack for Azure provides SQL Server Integration Services with the capability to connect to many Azure services, such as Azure Blob Storage, Azure Data Lake Store, Azure SQL Data Warehouse, and Azure HDInsight. It is a separate install, and you...

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Authors (6)

Parashar Shah

Parashar Shah is a Senior Program Manager in the Azure Machine Learning platform team.Currently, he works on making Azure Machine Learning services the best place to do e2e machine learning for building custom AI solutions using big data. Previously at Microsoft, he has been a Data Scientist and a Data Solutions Architect in various Cloud and AI teams. Prior to joining Microsoft, Parashar worked at Nokia Networks as a Solutions Architect & Product Manager building customer experience analytics solutions for global telcos. He also co-founded a carpooling startup, which helped employees carpool safely. He has 10+ years of global work experience. He is an alum of Indian Institute of Management, Bangalore and Gujarat University.

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Abraham

Peter Abraham has been a performance fanatic and a C/C++ programming language enthusiast right from his college days, where he excelled in Microsoft Windows programming and GNU Linux programming. He garnered experience in working with CUDA, image processing, and computer graphics programs by virtue of working with companies such as Quest Global, Siemens, and Tektronics. Peter has been eagerly following the C++ standard and RxCpp libraries as part of his profession. He has worked with cross-platform GUI toolkits such as Qt, WxWidgets, and FOX toolkit.

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Murphy

Ryan Murphy, one of the key Co-authors of Stream Analytics with Microsoft Azure is a Solution Architect living in Saint Louis, Missouri. He has been building and innovating with data for nearly twenty years, including extensive work in the gaming and agriculture industries. Currently, Ryan is helping some of the worlds largest organizations modernize their business with data solutions powered by the Microsoft Azure cloud.

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Lauri Lehman

Lauri Lehman is a data scientist who is focused on machine learning tools in Azure. He helps customers to design and implement machine learning solutions in the cloud. He works for the software consultancy company, Zure, based in Helsinki, Finland. For the past 4 years, Lauri has specialized in data and machine learning in Azure. He has worked on many machine learning projects, developing solutions for demand estimation, text analytics, and image recognition, for example. Lauri has previously worked as an academic researcher in theoretical physics, after obtaining his PhD on topological quantum walks. He still likes to follow the progress of modern physics and is eagerly a waiting the era of quantum machine learning!

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Jen Stirrup

Jen Stirrup is a data strategist and technologist, a Microsoft Most Valuable Professional (MVP), and a Microsoft Regional Director, a tech community advocate, a public speaker and blogger, a published author, and a keynote speaker. Jen is the founder of a boutique consultancy based in the UK, Data Relish, which focuses on delivering successful business intelligence and artificial intelligence solutions that add real value to customers worldwide. She has featured on the BBC as a guest expert on topics relating to data.

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Anindita Basak

Anindita Basak is a cloud architect with almost 15+ years of experience, the last 12 years of which she has been extensively working on Azure. She has delivered various real-time implementations on Azure data analytics, and cloud-native and real-time event-driven architecture for Fortune 500 enterprises, ranging from banking, financial services, and insurance (BFSI)to retail sectors. She is also a cloud and DataOps trainer and consultant, and author of cloud AI and DevOps books.

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