Machine Learning at Berkeley
@BerkeleyML
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Students at UC Berkeley working on academic research, ML education, industry projects, and fostering a vibrant ML community 🧠💡
Berkeley, CA
Joined December 2016
Great deep dive into TPUs with amazing visuals by our very own @henryHM_ko!.
I wrote a new blog on TPUs -- it's been fun seeing how different they are from GPUs and also drawing things on excalidraw again✏️.
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Join ML@B and the founders of the ARC Prize @fchollet and @mikeknoop to reveal techniques designed to defeat ARC-AGI- a $1M competition. Register for the event on Wednesday, October 2nd, 12-2 pm!
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ML@B is hosting our second-ever all day high school boot camp on the first weekend of September (8/31 to 9/1)! Applications are due Aug 17, 2024 and students can apply through
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⚡Introducing our free online course with @udacity and @googledevs—Gemini API by Google! Learn about LLMs, Gemini models, prompting techniques, and Google AI Studio. Enroll now: Read more from the Udacity CEO:
🚀 Level up your AI skills with the free new Gemini API course from @Udacity and Google! Get more familiar with LLMs and learn how to use Google AI Studio and the Gemini API to build AI applications. Enroll today to #BuildWithGemini →
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⚡Introducing our free online course with @udacity and @googledevs—Gemini API by Google! Learn about LLMs, Gemini models, prompting techniques, and Google AI Studio. Enroll now: Read more from the Udacity CEO:
🌟 Calling all developers – our new Gemini API by Google Course is live! . This FREE course is your gateway to mastering the integration of generative AI into your applications, websites, and services. @googledevs . Enroll in this free course today:
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RT @udacity: 🌟 Calling all developers – our new Gemini API by Google Course is live! . This FREE course is your gateway to mastering the in….
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Check out @alishbaimran's latest blog post delving into the application of ML in predicting protein structures, including insights on the newest AlphaFold model!.
How does AlphaFold3 predict the structures of proteins, DNA/RNA, ligands and other biomolecules? I did a deep dive into protein folding, how AlphaFold works and the new model. Here’s what I learned:. (resource in thread)
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Join us!.
We will be starting shortly! We'll get started with dinner in 10 mins, followed by the talk at ~7:20. If you can't make it in person to Berkeley, join remotely here!.
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RT @pdhsu: A wonderful profile of Arc's @BrianHie in this blog by @BerkeleyML. It traces his training in literary criticism and computer sc….
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New blog post from @CadeGordonML as part of a series highlighting emerging researchers! Give it a read :).
Research taste and vision can be challenging to craft. To help crystalize their role in science, I wrote a piece in @BerkeleyML's blog celebrating the young faculty @BrianHie who's been able to show a great blend of the two. Read it here:
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RT @CadeGordonML: I recently gave a talk to @BerkeleyML on Influence Functions through the lens of @AnthropicAI's recent work generalizing….
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RT @harbanijaggi: So awesome getting to meet @TheChainsmokers' Alex Pall and hearing about his journey in music and in venture! Thanks @jfi….
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Join us! Link to register in tweet below ⬇️.
Excited to host one of the most prolific people in science policy, @tkalil2050 for a chat in Berkeley on Monday, Feb 26. Come through! We'll talk datasets for bio, cost splitting for data collection, self-driving labs and much more!.
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RT @daveybloom: I had an incredible time talking about @TheHouseVC with 100+ future Berkeley founders last week. S/o @BerkeleyML for bringi….
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Very excited for this session - come out tomorrow 7pm!! Sign up below👇.
How can ML accelerate biological discovery? Join us and @BerkeleyML for an interactive discussion of our nematode embryogenesis classifier TOMORROW at 7pm!.
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Join us this Monday!.
Join us on Monday, Feb 12 for a seminar from the team at @ArcadiaScience, on how they've been using ML to accelerate biological discovery with their nematode embryogenesis classifier!.
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Come hear @aakarshv1 talk about machine learning for protein engineering! The talk will give an overview of AlphaFold2, RFDiffusion, and ProteinMPNN, three models that have been instrumental in the areas of protein structure prediction, and design.
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