Data in, intelligence out: https://
infoworld.com/article/225288
9/data-in-intelligence-out-machine-learning-pipelines-demystified.html
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Machine Learning in Microservices โ Productionizing microservices architecture for #MachineLearning solutions: http://
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Machine Learning Pipelines and Microservices Architecture for Production
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"Building AI Agents with LLMs, RAG, and Knowledge Graphs โ A practical guide to autonomous and modern AI agents" See it at http://
amzn.to/4622k2h via @PacktDataML -
Python Tools for Scientists: Anaconda, JupyterLab, Scientific Libraries
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#Python Tools for Scientists: An Introduction to Using Anaconda, JupyterLab, and Python's Scientific Libraries โโ Get it at http://
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Generative AI on Google Cloud with LangChain and Python
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Generative AI on Google Cloud with #LangChain โ Design scalable #GenerativeAI solutions with #Python, LangChain, and Vertex AI on Google Cloud: http://
amzn.to/4frbkPA v/ @PacktDataML ๐๐ฎ๐ ๐๐ฎ๐ช๐ฝ๐พ๐ป๐ฎ๐ผ:
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amzn.to/41jKa7r by @tng_konrad and @LucaMassaron โโโโโโ
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Machine Learning and Generative AI for Marketing with Python
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#MachineLearning and #GenerativeAI for Marketing using #Python โ http://
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New Book on AI Agents Design Implementation and Production Scaling
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See the latest book from @AltoValentina
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amzn.to/4p98LYl "AI Agents in Practice โ Design, Implement, and Scale Autonomous #AI Systems for Production" Book Description (from Amazon): As AI agents evolve to take on complex tasks and operate -
Building Production-Ready AI Agents with MLflow Evaluation
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๐งฑ Agent Bricks makes it easy to build high-quality, production-ready AI agents.
— Databricks (@databricks) 20 septembre 2025
In this demo by Kasey Uhlenhuth, youโll see how to:
-Build a knowledge assistant for document queries
-Evaluate with MLflow traces + custom metrics
-Improve answers with natural language feedbackโฆ pic.twitter.com/aKUWqMgWFCAgent Bricks makes it easy to build high-quality, production-ready AI agents. In this demo by Kasey Uhlenhuth, youโll see how to: -Build a knowledge assistant for document queries
-Evaluate with MLflow traces + custom metrics
-Improve answers with natural language feedback -
Master Trending AI Tech in 2025 โ Complete Learning Roadmap
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Master Trending AI Tech in 2025 โ Roadmap Fundamentals (1โ1.5 mo) Python | Data Analysis | Math for AI | Git | Cloud Basics Core Machine Learning (1.5โ2 mo) Supervised/Unsupervised | Pipelines | Model Monitoring | Feature Eng. Deep
