Machine Learning for Time Series with Python — Forecast, predict, and detect anomalies with state-of-the-art ML methods: http://
amzn.to/3wrjXVv by @benji1a —————
#DataScience #AI #Forecasting #PredictiveAnaytics #AnomalyDetection #IoT #IIoT #EdgeAI #EdgeComputing
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Book on ML for Time Series Forecasting and Anomaly Detection
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AA-Briefcase leaderboard for realistic tasks; Nemotron 3 Ultra top
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@ArtificialAnlys just dropped a brand new leaderboard called AA-Briefcase for evaluating realistic tasks in complex projects. Nemotron 3 Ultra ranks among the top open models, with strong performance across a wide range of long-running agentic tasks, even when encountering them -
Designing Machine Learning Systems – Iterative Process for Production
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Designing #MachineLearning Systems — An Iterative Process for Production-Ready Applications: http://
amzn.to/46epLSi by @chipro — 𝓣𝓸𝓹𝓲𝓬𝓼:
Engineering data and choosing the right metrics to solve a business problem Automating the process for continually developing, -
RAG-Driven Generative AI 2nd Edition: Build MAS-RAG with DualRAG
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New (2nd edition) from @PacktDataML available at http://
amzn.to/4tULP1b RAG-Driven Generative AI — Build MAS-RAG with DualRAG, GraphRAG, multimodal video pipelines, and Oracle Database 23ai 𝗞𝗲𝘆 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀:
Master DualRAG by combining vector search with SQL filtering -
LLM Engineer’s Handbook: Master LLM engineering from concept to production
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LLM Engineer's Handbook — Master the art of engineering Large Language Models LLMs from concept to production: http://
amzn.to/4dUQrv6 v/ @PacktDataML Implement robust data pipelines and manage LLM training cycles Create your own LLM and refine with the help of hands-on -
The defining metric of the 21st century: Intelligence per watt
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The defining metric of the 21st century is Intelligence per watt. (IPW)
— Nina Schick (@NinaDSchick) 26 juin 2026
The throughput of Intelligence divided by the power consumed to produce it. pic.twitter.com/wcixNgdA3UThe defining metric of the 21st century is Intelligence per watt. (IPW) The throughput of Intelligence divided by the power consumed to produce it.
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MCPs vs CLIs: Which to Use When Building Agents?
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Should you use MCPs or CLIs when building agents? @BraceSproul + @jakebroekhuizen spill the tea. pic.twitter.com/BjeEvzgjiU
— LangChain (@LangChain) 26 juin 2026Should you use MCPs or CLIs when building agents? @BraceSproul + @jakebroekhuizen spill the tea.
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@ornith_ model matches or beats Claude Opus 4.8
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HOLY SH*T this @ornith_ model is matching or even beating Claude Opus 4.8 I definitely need to move this up my priority list for a deep dive
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Model @ornith_ matches or beats Claude Opus 4.8 performance
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HOLY SH*T this @ornith_ model is matching or even beating Claude Opus 4.8 I definitely need to move this up my priority list for a deep dive
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NVIDIA and Zaha Hadid Architects Build Custom AI Tools for Secure Design
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AI is most impactful when it's tailored to the way teams already work. Discover how Zaha Hadid Architects uses local compute, fine-tuned AI models, and NVIDIA technologies to build custom AI tools that accelerate design while keeping proprietary data secure.