Deep Learning, Tips and Tricks in Machine Learning
RESEARCH
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Machine Learning Cheatsheets from Stanford’s CS 229
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Machine Learning cheatsheets from Stanford's CS 229:
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Microsoft Advances in Speech, Translation, Captioning, and NLP
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Hear about Microsoft's AI breakthroughs in speech recognition, machine translation, image captioning, and most notably, NLP. https://
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Smithsonian Institution Leverages AI for Data-Driven Insights
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The Smithsonian Institution is stepping into the future with data-driven AI projects. Mike Trizna of the Smithsonian Data Science Lab is leveraging AI to transform the Smithsonian's wealth of data into actionable insights. https://
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Key Metrics for Time Series Modeling and Regression
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important metrics for time series modeling and regression models
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LLMs as Compression: Underrepresented Languages Challenge
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> This also means that languages that are not well represented online typically aren't able to be compressed well you havent referred to the idea of llms as compression anywhere prior in the post overall good article!
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EU Digital Ambassadors Discuss AI, Chips, and Quantum Innovation
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When 23 digital EU ambassadors meet in Brussels, what do they talk about? #ArtificialIntelligence #chips #semiconductor #quantum #innovation #technology #digitaleu @DigitalEU @ArturHabant @elaniaz @PawlowskiMario @JolaBurnett @BetaMoroney @CurieuxExplorer @Shi4Tech @enilev… pic.twitter.com/uI9SNFncRH
— Nicolas Babin (@Nicochan33) 4 mai 2024When 23 digital EU ambassadors meet in Brussels, what do they talk about? #ArtificialIntelligence #chips #semiconductor #quantum #innovation #technology #digitaleu @DigitalEU @ArturHabant @elaniaz @PawlowskiMario @JolaBurnett @BetaMoroney @CurieuxExplorer @Shi4Tech @enilev
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Evalverse: Google Research Instruction Following Evaluation Submodule
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Super cool. FYI It's a submodule of evalverse forked from [google-research/instruction_following_eval](
https://
github.com/google-researc
h/google-research/tree/master/instruction_following_eval
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Request for more behind-the-scenes technical content and broader coverage
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the behind the scenes on claude thread you did was great, more like that anything @AmandaAskell or @benskuhn is good but also it doesnt gave to be an anthropic only newsletter. you have credibility if you can objectively discuss other stuff, including competing
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CUDA and C++ Origins Behind AlexNet’s Deep Learning Revolution
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# CUDA/C++ origins of Deep Learning Fun fact many people might have heard about the ImageNet / AlexNet moment of 2012, and the deep learning revolution it started. https://
en.wikipedia.org/wiki/AlexNet What's maybe a bit less known is that the code backing this winning submission to the