Friday, 18 July 2014

Azure Machine Learning–K Means Clustering…


 

 

imageimage

Machine Learning (ML) has been around almost over 5 decades now. In the last couple of years with the cloud computing and big data been the dominant colours in the IT Industry, ML has found a unique space in the Big Data problem.

A Brief on Azure ML

Azure ML is Machine Learning is simpler Microsoft offering from quick and easy ML advent. Its definitely a good starting point to get to use to the Machine Learning. As one may start using this more often will realize the Azure ML is limiting in terms of choices of Algorithms , data manipulation operations & ability to run as part to run with bigger scheme of things.

Most folks will start with Azure ML and figure out that there are multiple places where the constructs are limiting, so as a good citizen MSFT went and added the ExecuteR where one could program on R Studio for test and development, eventually for larger dataset, code port or intelligent copy to ExecuteR. A good video on how to use ExecuteR in Azure ML can be found here http://channel9.msdn.com/Blogs/Windows-Azure/R-in-Azure-ML-Studio

K-Means Clustering in Azure ML Video-

The data analysis starts of with initial task of having to classify data.  There are various algorithm which one may employ to classify data. The single most simplest and widely used algorithm is the K-Means Clustering. This session talks about K-Means Clustering and how to do the same using Azure ML.

The session take away from Azure ML is great not without R.

 

Files

Presentation Shared Here-https://drive.google.com/file/d/0B5lmX16jC3ZEcEprM2F0aW9FOVU/edit?usp=sharing

DataSets & Demo Here

RScripts - https://drive.google.com/file/d/0B5lmX16jC3ZES1c5MEdiamFCN0E/edit?usp=sharing

DataSets- https://drive.google.com/file/d/0B5lmX16jC3ZEY2R0T3R3WDU3NzQ/edit?usp=sharing

 

 

Reactions:

2 comments: