Hello Ankita, glad you liked the idea and thanks for the introduction; I'm not certain but I think you are the first with a background in computational biology.
The Essential deep learning modules project has been discussed at on the mailing list before: http://mlpack.org/pipermail/mlpack/2017-March/003107.html http://mlpack.org/pipermail/mlpack/2017-February/003092.html Note that there are many more posts on this in the mailing list archive to search for; those are only some places to get started. I hope this is helpful. Thanks, Marcus > On 22 Mar 2017, at 15:13, Ankita Shreya <[email protected]> wrote: > > 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. > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
