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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
Toc

Table of Contents (21) Chapters close

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

Inside ML Studio


You usually land at the ML Studio home page that contains a bunch of links to different resources, including documentation and quick-start videos.

Apart from ML Studio Home, you will also find the following tabs on the left-hand side of the screen:

  • EXPERIMENTS: These are the experiments that have been created, run, and saved

  • WEB SERVICES: This is a list of experiments that you have published

  • DATASETS: This is a collection of all the datasets that are either uploaded or saved from a experiment along with all the sample ones

  • TRAINED MODELS: This is a list of all the trained models

  • SETTINGS: This is a collection of settings that you can use to configure your account and resources

Experiments

You can think of an experiment as any analysis you would perform in ML Studio—it can be a simple one, such as a simple statistical analysis, or a complex predictive analysis. An experiment inside ML Studio is a collection of modules connected hierarchically. A module is a unit that encapsulates...

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