machine-learning-librarians-archivists
Introduction to AI for GLAM
https://github.com/carpentries-incubator/machine-learning-librarians-archivists
Science Score: 54.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○Academic publication links
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✓Committers with academic emails
4 of 16 committers (25.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.8%) to scientific vocabulary
Keywords
Repository
Introduction to AI for GLAM
Basic Info
- Host: GitHub
- Owner: carpentries-incubator
- License: other
- Language: Python
- Default Branch: main
- Homepage: https://carpentries-incubator.github.io/machine-learning-librarians-archivists/
- Size: 31.9 MB
Statistics
- Stars: 18
- Watchers: 9
- Forks: 15
- Open Issues: 35
- Releases: 2
Topics
Metadata Files
README.md
Intro to AI for GLAM
Our aim with this lesson is to empower GLAM (Galleries, Libraries, Archives, and Museums) staff with the foundation to support, participate in and begin to undertake in their own right, machine learning based research and projects with heritage collections.
After following this lesson, learners will be able to:
- Explain and differentiate key terms, phrases, and concepts associated with AI and Machine Learning in GLAM
- Describe ways in which AI is being innovatively used in the cultural heritage context today
- Identify what kinds of tasks machine learning models excel at in GLAM applications
- Identify weaknesses in machine learning models
- Reflect on ethical implications of applying machine learning to cultural heritage collections and discuss potential mitigation strategies
- Summarise the practical, technical steps involved in undertaking machine learning projects
- Identify additional resources on AI and Machine Learning in GLAM
Contributing
We welcome all contributions to improve the lesson! Maintainers will do their best to help you if you have any questions, concerns, or experience any difficulties along the way.
We'd like to ask you to familiarize yourself with our Contribution Guide and have a look at the more detailed guidelines on proper formatting, ways to render the lesson locally, and even how to write new episodes.
Please see the current list of issues for ideas for contributing to this
repository. For making your contribution, we use the GitHub flow, which is
nicely explained in the chapter Contributing to a Project in Pro Git
by Scott Chacon.
Look for the tag 
. This indicates that the maintainers will welcome a pull request fixing this issue.
Maintainer(s)
Current maintainers of this lesson are
- Mark Bell
- Nora McGregor
- Daniel van Strien
- Mike Trizna
Authors
A list of contributors to the lesson can be found in
Citation
To cite this lesson, please consult with
Owner
- Name: carpentries-incubator
- Login: carpentries-incubator
- Kind: organization
- Repositories: 107
- Profile: https://github.com/carpentries-incubator
Citation (CITATION)
FIXME: describe how to cite this lesson.
GitHub Events
Total
- Issues event: 5
- Watch event: 1
- Delete event: 1
- Issue comment event: 2
- Push event: 1
- Create event: 3
Last Year
- Issues event: 5
- Watch event: 1
- Delete event: 1
- Issue comment event: 2
- Push event: 1
- Create event: 3
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| noramcgregor | 3****r | 87 |
| Daniel van Strien | d****n | 61 |
| mark-bell-tna | m****l@n****k | 18 |
| Mike Trizna | t****m@s****u | 10 |
| Leigh | l****n | 3 |
| lawtlee | l****7@g****m | 3 |
| Benjamin Rosemann | b****n@l****e | 2 |
| Phil Reed | p****d@m****k | 2 |
| Annajiat Alim Rasel | a****t@g****m | 1 |
| RuthBurns | 4****s | 1 |
| Tim Dennis | t****s@l****u | 1 |
| Toby Hodges | t****s@g****m | 1 |
| Cody Hennesy | c****y@u****u | 1 |
| Marion Walton | t****n@g****m | 1 |
| aycasarez | a****z@g****m | 1 |
| ndalyrose | n****r@o****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 65
- Total pull requests: 38
- Average time to close issues: 10 months
- Average time to close pull requests: 27 days
- Total issue authors: 15
- Total pull request authors: 13
- Average comments per issue: 1.31
- Average comments per pull request: 0.47
- Merged pull requests: 36
- Bot issues: 15
- Bot pull requests: 0
Past Year
- Issues: 3
- Pull requests: 0
- Average time to close issues: 38 minutes
- Average time to close pull requests: N/A
- Issue authors: 2
- Pull request authors: 0
- Average comments per issue: 0.33
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- noramcgregor (23)
- github-actions[bot] (15)
- davanstrien (8)
- Naumann-Kai (3)
- chennesy (3)
- kjallen (3)
- leighphan (2)
- mark-bell-tna (2)
- tobyhodges (2)
- b2m (1)
- PhilReedData (1)
- amsichani (1)
- MikeTrizna (1)
- psteinb (1)
- jt14den (1)
Pull Request Authors
- davanstrien (14)
- MikeTrizna (6)
- mark-bell-tna (5)
- jt14den (3)
- b2m (2)
- leighphan (2)
- marionwalton (2)
- RuthBurns (2)
- noramcgregor (2)
- ndalyrose (1)
- aycasarez (1)
- zkamvar (1)
- annajiat (1)
- chennesy (1)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- github-pages >= 0 development
- actions/cache v1 composite
- actions/checkout master composite
- actions/setup-python v2 composite
- actions/setup-ruby main composite
- r-lib/actions/setup-r v2 composite
- actions/checkout master composite
- alstr/todo-to-issue-action v2.0 composite
- actions/cache v1 composite
- actions/checkout master composite
- actions/setup-python v2 composite
- actions/setup-ruby v1 composite
- r-lib/actions/setup-r v2 composite