https://github.com/alicerunsonfedora/abysima

A machine learning experiment with generating languages.

https://github.com/alicerunsonfedora/abysima

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (10.7%) to scientific vocabulary

Keywords

coreml generative-models keras lingustics recurrent-neural-networks swiftui
Last synced: 5 months ago · JSON representation

Repository

A machine learning experiment with generating languages.

Basic Info
  • Host: GitHub
  • Owner: alicerunsonfedora
  • License: mpl-2.0
  • Language: Jupyter Notebook
  • Default Branch: root
  • Homepage:
  • Size: 8.66 MB
Statistics
  • Stars: 2
  • Watchers: 2
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Topics
coreml generative-models keras lingustics recurrent-neural-networks swiftui
Created over 4 years ago · Last pushed about 4 years ago
Metadata Files
Readme License

README.md

Project Abysima

Welcome to the repository/notebook for Project Abysima. This notebook contains all of the notes and drafts for the project à la Markdown/Obsidian, as well as the Juptyer notebooks used to create the networks.

🏃🏻‍♂️ Quick Links

```ad-note title: Obsidian Linking

The quick links below use Obsidian's wiki-style linking format; links may not work correctly when viewing other Markdown editors or viewing this document in GitHub. The paths to the links are included as sub-bullet points in this list. ```

  • [[Linguistics Paper]]
    • 01 - Areas of Responsibility/Linguistics Paper
  • [[Annotated Bibliography]]
    • 03 - Resources/Annotated Bibliography

View the Jupyter Notebook →

ℹ️ What is Project Abysima?

Project Abysima is an attempt a creating a generative neural network that will devise its own language (not programming) based off of existing linguistic rules across languages. The main objective of the project is the following:

  • Can we get a machine learning algorithm to generate a language?
  • What linguistic properties can we use to improve these algorithms?
  • Can we make linguistics and linguistic properties easy to understand for a neural network?

🗄 General Organization

The organization of this project is broken down into four domains:

  • Projects contains series of tasks that are linked to a specific goal with a given deadline.
  • Areas of Responsibility contain a sphere of activity that will be maintained over time.
  • Resources contains themes, topics, and other notes of interest.
  • Archives contain archived data from the previously mentioned areas.

More information on this approach to project organization can be found at https://fortelabs.co/blog/para/.

Owner

  • Name: Marquis Kurt
  • Login: alicerunsonfedora
  • Kind: user
  • Location: Bear, DE

[mar.kɪs kɚrt] He/him. iOS app and game developer.

GitHub Events

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Last Year

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 62
  • Total Committers: 1
  • Avg Commits per committer: 62.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Marquis Kurt s****e@m****t 62
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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