Ex - Tesla. Kairos Society Fellow. SpaceX OpenLoop. TEDx speaker.
Code is one of the fundamental building blocks in machine learning research. Engineers already are in the habit of publishing code to share with the community, and it is now becoming standard for researchers to publish their code online as well. Increasingly more ML conferences are making it a requirement.
As David Ha (@hardmaru), a research scientist at Google Brain, puts it:
However, even if the code is actually available, you often have to go through the hassle of searching for it on Github manually or searching through various websites and blogs.
A new browser extension from CatalyzeX streamlines this whole process and automatically shows you open-source code for any machine learning/artificial intelligence papers that you may come across while you’re browsing the web — on Google, Arxiv, Twitter, Scholar, and other websites.
You’ll see [CODE] buttons appear in-line on the page automatically for any implementations found.
Click on any code link to easily jump to the code and explore.
If for some reason the code is not available, you can click on ‘NO CODE FOUND: REQUEST AUTHOR/EXPERT’
You’ll be redirected to here:
‘Ask Authors for Code’ will let you send a direct request for code to the authors — if they are willing to share it with you personally.
Sometimes the authors may choose to not make the code public.
In that case, feel free to click ‘Request Implementation’ and an expert on the topic can be requested to implement the paper instead.
P.S. — The creators of this extension reached out to Andrew Ng and he liked it too!
Install the Chrome extension here: https://chrome.google.com/webstore/detail/find-code-for-research-pa/aikkeehnlfpamidigaffhfmgbkdeheil
Install the Firefox extension here: https://addons.mozilla.org/en-US/firefox/addon/code-finder-catalyzex/
Also published on: https://himanshuragtah.medium.com/catalyzex-a-must-have-browser-extension-for-machine-learning-engineers-and-researchers-690b64ea3936
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