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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
Authors (2):
Sumit Mund Sumit Mund
Profile icon Sumit Mund
Christina Storm Christina Storm
Profile icon 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 ML Studio


ML Studio gives you an interactive visual workspace to easily build, test, and iterate a predictive analysis model.

You drag-and-drop datasets and analysis modules onto an interactive canvas, connecting them together to form an experiment, which you submit to ML Studio to run or execute. To iterate your model design, you edit the experiment, save a copy if desired, and submit it again.

There is no programming required for this; visually connecting datasets and modules to construct your predictive analysis model is enough. However, if you need more functionality than what is available visually in ML Studio out of the box, you can write R or Python code to get the desired result. R or Python programming is not an absolute must to work with ML Studio.

https://azure.microsoft.com/en-gb/documentation/articles/machine-learning-what-is-ml-studio/

Before you start working with ML Studio, you need to get a subscription for Microsoft Azure and sign in to ML Studio. The following...

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