Hello developers,
Hello Marcus,
Good to see mlpack in 2017’s organisation’s list. I am final year bachelor’s
student, will be joining Carnegie Mellon University as a graduate student this
fall with a specialisation in deep learning.
I had participated in GSoC 2015 with JdeRobot.
I also have done an internship from CMU Robotics institute on deep learning,
publication : https://www.ri.cmu.edu/pub_files/2016/11/cmu-ri-tr-Maturana.pdf
<https://www.ri.cmu.edu/pub_files/2016/11/cmu-ri-tr-Maturana.pdf>
Some of my relevant deep learning projects are:
https://github.com/shady-cs15/tiny-slash
<https://github.com/shady-cs15/tiny-slash> (generating guitar music with LSTM
nets)
https://github.com/shady-cs15/lrpr <https://github.com/shady-cs15/lrpr>
learning deep representations for place recognition (submitted, under review)
https://github.com/shady-cs15/rcnn <https://github.com/shady-cs15/rcnn> RCNNs
for scene labelling
I was looking for some projects related to deep learning in GSoC 2017 and the
two ideas in mlpack caught my attention.
1. Reinforcement learning
2. Essential deep learning modules
I had used mlpack previously. So I am somewhat familiar with the architecture.
Could you let me know about any warm up challenges or issues that need to be
patch in order to get started or before I start preparing my proposal.
Best,
Satyaki
(http://shady-cs15.github.io/ <http://shady-cs15.github.io/>)
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