deep-learning-intro
Learn Deep Learning with Python
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.0%) to scientific vocabulary
Keywords
Repository
Learn Deep Learning with Python
Basic Info
- Host: GitHub
- Owner: carpentries-lab
- License: other
- Language: Jupyter Notebook
- Default Branch: main
- Homepage: https://carpentries-lab.github.io/deep-learning-intro/
- Size: 43.6 MB
Statistics
- Stars: 37
- Watchers: 11
- Forks: 39
- Open Issues: 46
- Releases: 5
Topics
Metadata Files
README.md
Introduction to deep learning
This lesson gives an introduction to deep learning.
Teaching this lesson?
Do you want to teach deep learning? This material is open-source and freely available. Are you planning on using our material in your teaching? We would love to help you prepare to teach the lesson and receive feedback on how it could be further improved, based on your experience in the workshop.
You can notify us that you plan to teach this lesson by creating an issue in this repository or by sending an email to deep-learning-lesson-dev@esciencecenter.nl. Also, it would great if you can update this overview of all workshops taught with this lesson material. This helps us show the impact of developing open-source lessons to our funders.
Lesson Design
The design of this lesson can be found in the lesson design
Target Audience
The main audience of this carpentry lesson is PhD students that have little to no experience with deep learning. In addition, we expect them to know basics of statistics and machine learning.
Lesson development sprints
We regularly host lesson development sprints, in which we work together at the lesson. The next one is scheduled for the 13th and 14th of January 2025. We kickoff with an online meeting at 10:00 CEST. If you want to join (you are very welcome to join even if you have never contributed so far) send an email to deep-learning-lesson-dev@esciencecenter.nl .
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.
Please also familiarize yourself with the lesson design
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.
Setup the Workshop Website locally
To build this lesson locally, you should follow the setup instructions for the workbench. In short, make sure you have R, Git, and Pandoc installed, open R and use the following commands to install/update the packages needed for the infrastructure:
```r
register the repositories for The Carpentries and CRAN
options(repos = c( carpentries = "https://carpentries.r-universe.dev/", CRAN = "https://cran.rstudio.com/" ))
Install the template packages to your R library
install.packages(c("sandpaper", "varnish", "pegboard", "tinkr")) ```
Rendering the website locally
See the Carpentries Workbench usage instructions on how to render the website locally.
Maintainer(s)
Current maintainer of this lesson is
- Carsten Schnober (c.schnober@esciencecenter.nl)
Citation and authors
To cite this lesson, please consult with CITATION.cff. This also holds a list of contributors to the lesson.
Owner
- Name: The Carpentries Lab
- Login: carpentries-lab
- Kind: organization
- Repositories: 3
- Profile: https://github.com/carpentries-lab
GitHub Events
Total
- Create event: 41
- Release event: 3
- Issues event: 26
- Watch event: 5
- Delete event: 37
- Issue comment event: 77
- Push event: 113
- Pull request review event: 31
- Pull request review comment event: 15
- Pull request event: 46
- Fork event: 3
Last Year
- Create event: 41
- Release event: 3
- Issues event: 26
- Watch event: 5
- Delete event: 37
- Issue comment event: 77
- Push event: 113
- Pull request review event: 31
- Pull request review comment event: 15
- Pull request event: 46
- Fork event: 3
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 18
- Total pull requests: 29
- Average time to close issues: 5 months
- Average time to close pull requests: 2 months
- Total issue authors: 7
- Total pull request authors: 7
- Average comments per issue: 0.83
- Average comments per pull request: 1.28
- Merged pull requests: 16
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 16
- Pull requests: 27
- Average time to close issues: 3 months
- Average time to close pull requests: 20 days
- Issue authors: 7
- Pull request authors: 7
- Average comments per issue: 0.56
- Average comments per pull request: 0.85
- Merged pull requests: 16
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- ashwinvis (5)
- svenvanderburg (5)
- tobyhodges (4)
- brownsarahm (1)
- wirawan0 (1)
- angel-daza (1)
- code4yonglei (1)
Pull Request Authors
- qualiaMachine (8)
- tobyhodges (7)
- svenvanderburg (6)
- angel-daza (3)
- ashwinvis (2)
- carschno (2)
- matt-graham (1)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- github-pages >= 0 development
- actions/checkout v2 composite
- actions/setup-python v2 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
- 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