deep-learning-intro

Learn Deep Learning with Python

https://github.com/carpentries-lab/deep-learning-intro

Science Score: 36.0%

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
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  • DOI references
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
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  • Scientific vocabulary similarity
    Low similarity (13.0%) to scientific vocabulary

Keywords

carpentries carpentries-lab deep-learning deep-neural-networks dollar-street english keras lesson neural-network python stable
Last synced: 6 months ago · JSON representation

Repository

Learn Deep Learning with Python

Basic Info
Statistics
  • Stars: 37
  • Watchers: 11
  • Forks: 39
  • Open Issues: 46
  • Releases: 5
Topics
carpentries carpentries-lab deep-learning deep-neural-networks dollar-street english keras lesson neural-network python stable
Created about 7 years ago · Last pushed 6 months ago
Metadata Files
Readme Contributing License Code of conduct Citation Authors

README.md

Binder DOI The Carpentries Lab Review Status

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 good_first_issue. 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

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

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
Episode 2 (2) lesson-dev-sprint (2) type:clarification (1)
Pull Request Labels
type: template and tools (1)

Dependencies

Gemfile rubygems
  • github-pages >= 0 development
.github/workflows/inline-code.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
.github/workflows/template.yml actions
  • 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
.github/workflows/website.yml actions
  • 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