arrow_back Splunk> Driving Real-time Analytics from Small Data, Big Data and Huge Data
Approaches to ML techniques on the Real world data.
Submitted by Venkata Ramana (@ramana) on Monday, 28 May 2012
Section: Data Analytics Technical level: Intermediate Session type: Demo
Learn how to think in applying ML techniques, and the practical aspects of it.
List out possibilities of applying various Machine Learning Techniques to Real World Data. It focuses on what (are available ?), why (to use one or some of them ?) and how (to apply for the problem in hand ?)
A demo on one/more Real world use cases. This can help an enthusiast to start on .... without digging noise!
A useful scenario would be to learn behavioural patterns in social networks. Say, an algorithm that you can train to judge your friends. So you can get some insight in your intutive behaviour on the web ;) You can apply these rules may be in training a larger set of your own activities.
You must have an enthusiasm to ask how? and why? things do/ do not happen and keep it simple and clear.
Knowledge of Python. Basics of Machine Learning Algorithms is a plus.
I am a python developer at Agiliq. I hold Master's degree as a Knowledge Engineer. I wonder how things fit to do some Good work. The best way to be productive is to be practical.