[mlpack] Automative benchmarking

[Ranjani]

Hi,
I am Shree Ranjani ,a final year Computer Science student from India.

I am really interested in continuing the work on "*Automative benchmarking
of mlpack methods*".
I have been playing around with mlpack libraries quite a bit and also ran
benchmarking scripts for some algorithms.I have been going through the
discussions on this project and find that the following ideas should be
given more priority more than others

1.Given a specific time frame ,which is the fastest running time.
2.Benchmarking in distributed environment.
Also,I feel that the benchmarking scripts can also be extended to
classification algorithms like SVM,Bayesian as well.

It would be really nice if you could give a clear idea about the
integration with Shogun in this project.

Mentioning more about myself - I am pretty comfortable writing codes in
Python,C++. I have done a research internship in NetApp,India on a machine
learning project.
I am really interested in *Machine learning ,Data Mining and NLP* and all
my academic projects were in this area.Some of them are
1.Developed an Intelligent Classroom system that automated subjective
question and answer evaluation and provided feedback to teachers about
students' performance
2.Working on Strength of Sentiment analysis of movie data using NLP
techniques
I have taken up courses on Artificial Intelligence,Data Mining and Machine
learning during my course curriculum.


Do let me know,so that i can start working asap! :)

-- 
Regards,
Shree Ranjani
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