After you are happy with a particular model, save it as a trained model and then prepare an experiment for a web service and proceed to deploy the model. Refer to Chapter 11, Publishing a Model as a Web Service, to find the details on how to deploy a model to the staging environment and test it visually in ML Studio.
Microsoft Azure Machine Learning
By :
Microsoft Azure Machine Learning
By:
Overview of this book
Table of Contents (21 chapters)
Microsoft Azure Machine Learning
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
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
Customer Reviews