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DeepLearnR tensorFlow Object system for R
Enhance the R package to interface with DeepLearning Frameworks, specifically Google's TensorFlow. DeepLearning is a broad subject and this work would focus on a subset of features that add value to the R community for example a scalable implementation of CovNets & LSTM.
Currently there are no other packages. We are working on a package deepLearnR which implements initial features via rPython and skflow. The work on this GSOC proposal would be to enhance that package.
R interfaces, datasets, vignettes and demos
Interfaces to scalable deep learning frameworks is an essential capability to the R community. The bigger idea for the DeepLarnR package is to create a complete "wrapper" for TensorFlow probably starting with rPython eventually with rcpp as the c++ layer gets more richer interfaces
Krishna Sankar
Each project needs 2 mentors. Ideally one should be an expert R programmer with previous package development experience, and the other can be a domain expert in some other field or application area (optimization, bioinformatics, machine learning, data viz, etc).
Note : I will add tests
Several tests that potential students can do to demonstrate their capabilities for this particular project. Please modify the suggestions below to make them specific for your project.
- Easy: something that any useR should be able to do, e.g. download some existing package listed in the Related Work, and run it on some example data.
- Medium: something a bit more complicated. You can encourage students to write a script or some functions that show their R coding abilities.
- Hard: Can the student write a package with Rd files, tests, and vigettes? If your package interfaces with non-R code, can the student write in that other language?
Students, please post a link to your test results here.