Caffe deep neural networks - rstats-gsoc/gsoc2018 GitHub Wiki

Deep neural networks are powerful supervised learners for large labeled data sets. One implementation of these models is provided by the Caffe open-source C++ library.

The nnet package implements single layer neural networks. Caffe implements multi-layer (deep) neural networks. MENTORS: you should provide a detailed description of what Caffe provides over existing R packages for deep learning such as deepnet.

Other projects that use the Caffe C++ code are listed on their wiki.

Write an R package that interfaces the Caffe C++ code. It should implement the same functionality as the Python and MATLAB packages discussed on the Caffe Interfaces page.

mentors: please fill in.

There are currently no mentors for this project. Ideally there should be one mentor who is an expert in R package development and another mentor who is an expert user or developer of the Caffe C++ code. Any interested students should first try to find a mentor from the caffe community by emailing caffe-users and then, once they find a mentor, email the gsoc-r list to explain who they found, and try to find a mentor in the R community. TD Hocking would consider mentoring this project, if a suitable mentor was found from the Caffe community.

Do one or several — doing more hard tests makes you more likely to be selected.

• MENTORS: post tests for students here.

Students, please post a link to your test results here.