[mlpack] Interested in Essential Deep Learning Modules- Radial Basis Function Network

Ankita Shreya ankita9shreya at gmail.com
Wed Mar 22 10:13:09 EDT 2017


Hi,

I am Ankita Shreya , a second year CSE student from IIIT Bhubaneswar. I
have a strong desire in coding and  have solved some challenging problems
in the area of computational biology. I generally use machine learning
approach as these approaches are robust to handle biological data which are
generally prone to noise. As machine learning is an emerging area of
research so my interest in this area developed in second year.I have
undertaken Machine Learning Course from Coursera by Prof. Andrew Ng. I
initiated my work by solving the micro-array classification problem where I
have used Probabilistic Neural Network as the classifier. As this data is
of high dimension, so filters and wrapper are used for significant feature
extraction. As I am undertaking Design and Analysis of Algorithm course in
this semester,I have come to know that the computational time complexity
for every model is a major concern. The accuracy of the classification
problem is also a major factor to justify the goodness of the model. Google
Summer Code can give me an opportunity by providing me a platform where I
can explore the various learning paradigms of RBFN.  I am very much curious
to get myself started with the Essential Deep Learning Modules- Radial
Basis Function Network. I have been busy these days  with my university
exams and now as they are over I have started reading those suggested
papers.
Looking forward for your reply.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://knife.lugatgt.org/pipermail/mlpack/attachments/20170322/7ac6d526/attachment.html>


More information about the mlpack mailing list