Linear Algebra and Optimization for Machine Learning [516-page textbook]: http://
amzn.to/39aWf8N
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#DataScience #DataScientist #ML #Mathematics #ORMS
MACHINE LEARNING
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Linear Algebra and Optimization for Machine Learning textbook announcement
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Book recommendation: AI Agents in Practice by Valentina Alto
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Another great book by @AltoValentina
, from @PacktDataML at http://
amzn.to/4p98LYl "AI Agents in Practice — Design, Implement, and Scale Autonomous #AI Systems for Production" Book Description (from Amazon): As AI agents evolve to take on complex tasks and operate -
New Book: Unlocking Data with Generative AI and RAG, 2nd Edition
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2nd Edition, by @keithbourne v/ @PacktDataML "Unlocking Data with Generative AI and RAG — Learn AI Agent Fundamentals with RAG-powered Memory, Graph-based RAG, and Intelligent Recall" Get the book here: http://
amzn.to/49zsIkb -
Business Value of Agentic AI: Three Key Pillars
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What's The #Business Value Of #AgenticAI? Three Key Pillars For Scaling #AIAgents
by Preetpal Singh @Forbes Learn more: https://
buff.ly/Ax4IOkO #LLM #GenerativeAI #ArtificialIntelligence #MachineLearning -
MeMo: Separate Memory Architecture for Language Models
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Researchers just gave LLMs a separate brain for memory. Language models go stale the moment training ends. Updating them risks breaking what they already know. A new paper proposes MeMo. It pairs any LLM with a separate trained memory model. The base model stays frozen.
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Boring context compaction beats multi-agent systems for most use cases
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I've built multi-agent systems for clients. I still think they're overrated for most use cases. What's underrated is boring. Context compaction. The reason your AI app feels slow and expensive isn't the model. It's everything you keep stuffing into the prompt before it even
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How AI Agents Manage Goals and Objectives
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How #AIAgents Manage Goals and Objectives
by @e_opore #AI #LLM #ArtificialIntelligence #MachineLearning #ML -
C++ Inference Engine for NVFP4 without MTP
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I believe this is without MTP C++ Inference Engine that's highly optimized for NVFP4
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Screenshot of new inference engine by @AlpinDale
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Screenshot from the new Inference Engine @AlpinDale is working on
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Why Large Language Models Speak and Think Like Humans
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Why can large language models speak and think like humans? Link: https://
github.com/hangli-hl/AI-A
rticles/blob/main/.pdf
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