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Join GitHub (or sign in) to find projects, people, and topics catered to your interests.
Here's what's popular on GitHub today...
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Mastodon
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Jun 7, 2020 - JavaScript
Capture the Flag
May 06, 2020 - June 12, 2020 • Online
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Text editors
The text editor is a sacred application for developers. Here's a showcase of some amazingly awesome open source editors.
AccessLint
AccessLint brings automated web accessibility testing into your development workflow. When a pull request is opened, AccessLint reviews the changes and comments with any new accessibility issues, giving you quick, timely, and targeted feedback, before code goes live.
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Jun 5, 2020 - Java
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May 29, 2020 - Java
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Contributing.md doesn't doesn't appear to contain any actual guidlines, and the link only leads back to the same document: Java/CONTRIBUTING.md.
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I think "outputs [-1]" and "outputs [0]" are equivalent (reversed) in this line of code, but the former (89%) works better than the latter (86%). Why?
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Apr 29, 2020 - Jupyter Notebook
There are some interesting algorithms in simulation from Physics, Chemistry, and Engineering especially regarding Monte Carlo simulation: Heat Bath algorithm, Metro-Police algorithm, Markov Chain Monte Carlo, etc.
Skill Set Challenge!
Hudson & Thames has provided the following skillset challenge to allow potential researchers to gauge if they have the required skil
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Jun 7, 2020 - Python
DeepAffects
Managing teams to deliver projects/products on time is hard, but figuring out where your team collaboration is lacking can be even more painful. DeepAffects analyzes emotions and tones in issue description and comments to provide actionable insights to identify the high-resolution time issues, disagreements in the team.
DeepAffects is a team dynamics analytics application, for managers & team leads, to get issue-level emotional insights, to increase team dynamics & productivity.



Right now, the integration test use the movie dataset. This is an issue because this dataset is unnessecarily big for testing purpose and thus drastically slows down running the test suite. I suggest we use a smaller dataset (< 100 entries) to improve our CI time.