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https://github.com/andreasmadsen/master-thesis

Semi-Supervised Neural Machine Translation - for small bilingual datasets

https://github.com/andreasmadsen/master-thesis

Science Score: 13.0%

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Keywords

machine-learning natural-language-processing neural-machine-translation neural-network thesis
Last synced: 5 months ago · JSON representation

Repository

Semi-Supervised Neural Machine Translation - for small bilingual datasets

Basic Info
  • Host: GitHub
  • Owner: AndreasMadsen
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 17.3 MB
Statistics
  • Stars: 9
  • Watchers: 2
  • Forks: 2
  • Open Issues: 0
  • Releases: 0
Topics
machine-learning natural-language-processing neural-machine-translation neural-network thesis
Created about 9 years ago · Last pushed over 8 years ago
Metadata Files
Readme

README.md

Master Thesis

Semi-Supervised Neural Machine Translation - for small bilingual datasets

By: Andreas Madsen (June 2017)

Download

shell git clone https://github.com/AndreasMadsen/master-thesis.git

Code

Dependencies

The code was written using: * Python 3.6 * TensorFlow 1.1 * Sugartensor. Some of my PRs haven't been merged yet, for now use: https://github.com/AndreasMadsen/sugartensor/tree/master-thesis * tqdm * numpy * scipy * R and ggplot2

Run code

All the experiments ( and may more :o ) are in the code/script directory, the plot generation code is in code/plot. The jobs and grid directory is for running on the DTU LFS queue system.

Dataset

The datasets are automatically downloaded, primarily Europarl v7 and WMT NewsTest are used.

Code License

The code license is MIT and is seperate from the main thesis license.

Copyright (c) 2017 Andreas Madsen

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Report

The report is build using make report.

The figures are available as Incscape files. The Incscape files uses Modern Latin Roman as the font, so make sure to have that installed.

Report License

While the LaTeX code is available it is not open source. That means you are not allowed to redistribute or modify the PDF, the LaTeX code, or any other file. But you can redistribute this url: https://github.com/AndreasMadsen/master-thesis

Owner

  • Name: Andreas Madsen
  • Login: AndreasMadsen
  • Kind: user
  • Location: Copenhagen, Denmark
  • Company: MILA

Researching interpretability for Machine Learning because society needs it.

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