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Caffe deep neural networks

Toby Dylan Hocking edited this page Jan 28, 2016 · 6 revisions

Background

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.

Related work

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.

Coding project: library(caffe)

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.

Expected impact

mentors: please fill in.

Mentors

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 try to find two mentors by sending emails to the caffe-users and gsoc-r lists.

Tests

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

  • MENTORS: post tests for students here.

Solutions of tests

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

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