In roughly all of my experience (Geoff/Ruslan RBM work at UofT, Nando lab at UBC, Andrew Ng lab at Stanford, my 2011 Google internship in baby Google Brain, and ~all computer vision work I was familiar with) it was all only Matlab. I’ve never used Theano but I used Torch in
MACHINE LEARNING
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Daily content sharing on Python, Data Science, and Machine Learning
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That's a wrap! If you are interested in any of these below topics: – Python – Data Science – Machine Learning – Data Analysis – LLMs – MLOps Find me → @Sumanth_077 I'm sharing daily content over here.
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Deep Learning and Machine Learning Tips and Tricks
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Deep Learning, Tips and Tricks in Machine Learning
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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://
buff.ly/3JJXjip -
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://
buff.ly/3UE0sqa -
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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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 -
Professor Cordelia Schmid Wins Monte-Carlo Woman Year Award
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Congratulations on the well-deserved recognition to my colleague, @CordeliaSchmid
! "The Monte-Carlo International Woman of the Year Award was presented by Princess Stephanie of Monaco to Professor Cordelia Schmid, a world leading specialist in computer assisted recognition, -
RAG versus fine-tuning: Understanding key AI training approaches
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That sounds like RAG, not fine-tuning