2016 Ruby Association Grant selection result

We are very happy to announce that the following four projects have been selected by the Ruby Association grant committee.
Accomplishments of the projects will be published around March 2017.  

Ruby System for Elementary Statistical Analysis

 Project summary

 We aim to “make Ruby a practical language in data science” and “develop and build an elementary statistical analysis pipeline”.  Although some gems for data science such as Nyaplot or Daru has been developed, these gems are not yet widely used. The main causes are "immatureness of gem cooperation" and "lack of document". For example, practical examples combining multiple packages are provided with detailed document, and there is no concern about these points in Python.  Through the statistical analysis pipeline we will create a guide showing how to combine Ruby gems and how to input, analyze and visualize data. In addition we will improve existing gems and make cooperation between gems easier as well.

 Applicant name

  Yoshihiro Ashida 
  Yusuke Sangenya 
  Kozo Nishida

Subproject libraries for Ruby/Numo

 Project summary

  I'll implement a linear algebra library and a GSL library for NArray / Ruby Numo. The library numo-lapack will provides direct interface to LAPACK, and equivalent functionality which NumPy's linalg.

 Applicant name

 Makoto Kishimoto

Tensorflow.rb

 Project summary

 This project aims at making Tensorflow.rb completely compatible with Tensorflow C API. Currently many interesting developments are taking place in Tensorflow and by the end of the project all the functionalities of the C API of Tensorflow must be easily accessible from the Ruby API.

 Applicant name

   Arafat Khan

Rubex - A new language for writing Ruby extensions

 Porject summary

 Rubex is basically a superset of the Ruby Programming Language that will allow users to write Ruby C extensions for the CRuby interpreter without having to leave the comfort of Ruby.

To summarize, the objectives of the Rubex project are as follows:

 Applicant name
 Sameer Deshmukh