9/ Survey of LLMs – reviews three popular families of LLMs (GPT, Llama, PaLM), their characteristics, contributions, and limitations; includes a summary of capabilities and techniques developed to build and augment LLM.
MACHINE LEARNING
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V-JEPA: Self-Supervised Vision Model Trained on Two Million Videos
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3/ V-JEPA – vision models trained on a feature prediction objective using 2 million videos; relies on self-supervised learning and doesn’t use pretrained image encoders, text, negative examples, reconstruction, or other supervision sources.
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Top ML Papers Week: Sora, Gemini 1.5, Agents
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The Top ML Papers of the Week (Feb 12 – Feb 18): – Sora
– Gemini 1.5
– OS-Copilot
– TestGen-LLM
– Large World Model
– LLM Agents can Hack
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Free MIT Linear Algebra Course for Machine Learning Foundations
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Arguably, the best Linear Algebra course out there for Machine Learning! Taught by MIT's Professor Gilbert Strang. And it's FREE! Build a strong foundation in mathematics for machine learning: https://
youtube.com/playlist?list=
PL221E2BBF13BECF6C
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OMNI: Open-endedness Models Human Notions Interestingness
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OMNI: Open-endedness via Models of human Notions of Interestingness Zhang et al.: https://
arxiv.org/abs/2306.01711 #ArtificialIntelligence #DeepLearning #MachineLearning -
OMNI: Open-endedness Models Human Interestingness Notions
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OMNI: Open-endedness via Models of human Notions of Interestingness Zhang et al.: https://
arxiv.org/abs/2306.01711 #ArtificialIntelligence #DeepLearning #MachineLearning -
Python Data Science Machine Learning MLOps Tutorials Daily
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That's a wrap! If you interested in: – Python – Data Science – Machine Learning – Maths for ML – MLOps – CV/NLP – LLMs Find me → @akshay_pachaar Everyday, I share tutorials on above topics! Check my tutorial on Self-Attention
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Stanford CS25 Transformers United Course Overview
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Stanford CS25 – Transformers United Since their introduction in 2017, transformers have revolutionised the world of NLP! This course delves into the inner workings of transformers, exploring their applications with a focus on LLMs. Check this out
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ML on Graphs: Learn Network Structure Analysis
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ML on Graphs This course covers important research on the structure & analysis of large social & information networks. I have personally learnt a lot from this course & it helped me solve problems where traditional methods failed. Check this out https://
youtube.com/playlist?list=
PLoROMvodv4rPLKxIpqhjhPgdQy7imNkDn
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Reinforcement Learning Course Introduction with Lecture Videos
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Reinforcement learning This class will provide a solid introduction to the field of reinforcement learning. You'll learn through a combination of lectures, & written and coding assignments. Check this out https://
youtube.com/playlist?list=
PLoROMvodv4rOSOPzutgyCTapiGlY2Nd8u
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