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Microsoft Azure Machine Learning

You're reading from Microsoft Azure Machine Learning

Product type Book

Published in Jun 2015

Publisher

ISBN-13 9781784390792

Pages 212 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Authors (2):

Sumit Mund

Christina Storm

View More author details

Table of Contents (21) Chapters

Microsoft Azure Machine Learning

Credits

About the Author

Acknowledgments

About the Reviewers

www.PacktPub.com

Preface

Introduction

ML Studio Inside Out

Data Exploration and Visualization

Getting Data in and out of ML Studio

Data Preparation

Regression Models

Classification Models

Clustering

A Recommender System

Extensibility with R and Python

Publishing a Model as a Web Service

Case Study Exercise I

Case Study Exercise II

Index

Introduction to R

R is an open source statistical programming language and in recent years, it has been hugely popular. R has significant and vibrant communities worldwide and it is rich with libraries/packages, which get new additions every day. R is a first-class citizen in the Azure ML land, meaning that it has its native support for the language. Among many data structures, R has the data.frame data structure, which can be assumed to be a data table with rows and columns with column headers. Though there are differences, you can safely think of it as a dataset in ML Studio. So, whenever a dataset is passed to R code in an experiment, it implicitly gets converted to the data.frame data structure.

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Authors (2)

Sumit Mund

Sumit Mund is a BI/analytics consultant with about a decade of industry experience. He works in his own company, Mund Consulting Ltd., where he is a director and lead consultant. He is an expert in machine learning, predictive analytics, C#, R, and Python programming; he also has an active interest in Artificial Intelligence. He has extensive experience working with most of Microsoft Data Analytics tools and also on Big Data platforms, such as Hadoop and Spark. He is a Microsoft Certified Solution Expert (MCSE in Business Intelligence). Sumit regularly engages on social media platforms through his tweets, blogs, and LinkedIn profile, and often gives talks at industry conferences and local user group meetings.

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Christina Storm

contacted on 5 aug 16

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