
Mining insights in data science, machine learning, analytics, and AI • Edited by @mattmayo13 • KD stands for "knowledge discovery"
San Juan, PR
Joined February 2009
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A JSON pipeline for ML configs that survives datetime, set, Path and Enum: a custom encoder, an object_hook decoder that fails gracefully, and a factory that migrates old schemas. #Python
machinelearningmastery.com/r…
Do you need an AI agent or a workflow with an LLM step? One practical test and a five-point checklist to answer that before you write any code. #AIAgents
machinelearningmastery.com/a…
7 Python design patterns for data science code, from Strategy for swappable metrics to Command for replayable runs as frozen dataclasses. Each comes with the caveat that keeps it honest. #Python
kdnuggets.com/7-advanced-pyt…
Multi-agent systems cost latency, tokens and debugging time. The four conditions where that complexity is worth it, and a framework for deciding. #AIAgents
machinelearningmastery.com/s…
Build a Python agent with the OpenAI Agents SDK that searches the web, calls your own functions as tools and remembers the conversation in SQLite, with no hand-written tool loop. #AIAgents
kdnuggets.com/building-your-…
One API, many models: use OpenRouter from Python to compare GPT, Claude and Llama, switch models with one string, and add fallbacks. Every example runs on free models.
kdnuggets.com/access-multipl…
A 600M parameter model that runs offline on a laptop CPU and only cleans up transcripts, never rewriting what you said. What makes SuperWhisper's open-weight S1-mini different. #SpeechToText
kdnuggets.com/superwhisper-s…
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Join Google Cloud for Trusted Agents, Real Outcomes and explore how Agentic Data Cloud can help turn enterprise data into a foundation for reliable AI workflows.
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Turn data into decisions that matter
Earn an M.S. in Business Analytics at Georgetown.
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Interested in building AI agents that deliver real business results?
Google Cloud's Trusted Agents, Real Outcomes online event explores how modern data infrastructure can support trusted, autonomous AI workflows.
A relevant session for data engineers, AI developers, and technology leaders looking to scale enterprise AI.
📅 November 5 | 10 AM CET (EMEA)
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Cohere caught Alibaba’s Qwen model unexpectedly attempting to upload a test payload to Alibaba Cloud storage during a cybersecurity task, but the sandbox blocked the request, leaving questions about what triggered the b... f.mtr.cool/9kvh1qsjvx
A data-backed guide to the credentials that actually move the needle for data scientists and machine learning practitioners. f.mtr.cool/ewjsg50f6t
Vibe coding is a workflow where you describe what you want in natural language and let an AI agent handle code generation, execution, and iteration rather than typing every line yourself. f.mtr.cool/1cmfq6g7pb
4 bugs that pass every null check, duplicate check, and schema test. f.mtr.cool/r7ck2cgsdt
[Nov 5 Webinar] The Agentic Operating Model with LangChain
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💡 Building an AI prototype is one thing. Making it work across an enterprise is another.
To deliver real value, AI agents need reliable access to data, strong governance, and infrastructure that can scale.
Join Google Cloud to explore how its Agentic Data Cloud approach can help organizations move toward more dependable, production-ready AI workflows.
📅 November 5 | 10 AM CET (EMEA)
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#EnterpriseAI #AIInfrastructure #AgenticAI
Which AI skills appear most often in job postings right now, and what do they mean for your career? f.mtr.cool/5fv68tbwhp
Learn which five Docker containers make a reliable home AI lab, from Ollama and Open WebUI to Qdrant, n8n and Portainer CE, what job each one does, and the first mistake to avoid with each. f.mtr.cool/hr46wkgbhk
Learn how to get started with the OpenRouter API to call multiple AI models through one API, compare responses, switch models, and set up automatic fallbacks. f.mtr.cool/66qn18gyxr
[Oct 29 Webinar] The Agentic Operating Model with LangChain
bit.ly/4e04D9d


