Build your first AI Agent with Gemini, n8n and Google Cloud Run https://
buff.ly/zEKdNgk
#AI #MachineLearning #DeepLearning #LLMs #DataScience
MACHINE LEARNING
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Build Your First AI Agent with Gemini, n8n, Cloud Run
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Building AI Startups: Innovation, Risk, and Strange Ideas
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How to Build an AI Startup: Go Big, Be Strange, Embrace Probable Doom
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @timnitgebru @oriolvinyalsml @ceobillionaire @soumithchintala @waitin4agi_ @sallyeaves @bernardmarr -
Recommended book: Mastering Machine Learning Algorithms
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Brilliant 798-page book explains “every #ML algorithm from A to Z” — I have a copy and love it! >> "Mastering #MachineLearning Algorithms" at http://
amzn.to/37cDZ7F by @GiuseppeB — #Python #DeepLearning #AI #DataScience #Mathematics #Calculus #DataScientist -
Mastering spaCy: Build NLP Solutions with spacy-llm
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Mastering spaCy — Build structured NLP solutions with custom components & models powered by spacy-llm: http://
amzn.to/3QpPfXi v/ @PacktDataML [2nd edition] 𝓦𝓱𝓪𝓽 𝔂𝓸𝓾 𝔀𝓲𝓵𝓵 𝓵𝓮𝓪𝓻𝓷:
Apply transformer models and fine-tune them for specialized NLP tasks
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Technical discussion on 3D Gaussian Splatting registration and automation
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very nice; how do you handle 3dgs google 3d tiles registration? manual or have you come up with an automated approach? thinking of ortho matching – tho for that you prolly also wanna clean up those floaters first
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Data Architecture Upside Down – PyData Amsterdam 2025
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KEYNOTE: Hannes Mühleisen – Data Architecture Turned Upside Down | PyData Amsterdam 2025 https://
buff.ly/tWYfXMG
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Computer Vision and the Future of Immersive Sports Broadcasting
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The tech we use to capture sports is a decade ahead of how we actually watch it. We can reproduce entire games in 3D, track every player down to their pose and heartbeat – but barely any of that makes it to your living room.
— Bilawal Sidhu (@bilawalsidhu) 7 février 2026
0:00 Immersion Gap
0:48 Computer Vision & Hawk-Eye… pic.twitter.com/jgRwnrELeuThe tech we use to capture sports is a decade ahead of how we actually watch it. We can reproduce entire games in 3D, track every player down to their pose and heartbeat – but barely any of that makes it to your living room. 0:00 Immersion Gap
0:48 Computer Vision & Hawk-Eye -
HunyuanOCR Technical Report on Advanced Character Recognition
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HunyuanOCR Technical Report https://
bit.ly/4bkGbyA
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Computer vision integration in sports broadcasting replays
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sony's hawk eye cameras are used for VAR (video assisted referee) which heavily rely on computer vision. but only now is that data feed being explored to surface in replays (which is nuts to me)
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Agentic Architectural Patterns for Multi-Agent GenAI Systems
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New release v/ @PacktDataML @PacktPublishing "Agentic Architectural Patterns for Building Multi-Agent Systems: Proven design patterns and practices for GenAI, agents, RAG, LLMOps, and enterprise-scale AI systems" See it at http://
amzn.to/3MaHy8T 𝕋𝕒𝕓𝕝𝕖 𝕠𝕗