The architecture behind a portable knowledge layer and the automation that keeps it alive.
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ChatGPT is Now Inside Excel and Google Sheets: Here is How to Use it
AI technology is leapfrogging, yet that doesn’t mean we always want a revolutionary feature out of it. What most users would want more of are simple capabilities within AI that can help with their everyday tasks, whether in the office, at home, or anywhere else. On those lines, OpenAI may have just ...
Abacus AI Review: Features, AI Agents & Automation Explained (Honest Guide)
A detailed Abacus AI review covering ChatLLM, Abacus AI Agent, Claw, automation, app building, image and video generation, pricing, pros, cons, and who should use it.
Beyond Lists: Using Python Deque for Real-Time Sliding Windows
Stop shifting elements in lists! Discover why collections.deque is the secret to high-performance sliding windows, thread-safe queues, and efficient data streams in your next Python project.
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Why I Don’t Trust LLMs to Decide When the Weather Changed
A physicist's approach to building production-grade agents
The post Why I Don’t Trust LLMs to Decide When the Weather Changed appeared first on Towards Data Science.
Deconstruct Any Metric with a Few Simple ‘What’ Questions
What you see is rarely what you get with flashy dashboards and data storytelling
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Improve Claude Code performance by having it validate its own work
The post How to Make Claude Code Validate its own Work appeared first on Towards Data Science.
Top 10 Open-Source Libraries to Fine-Tune LLMs Locally
Fine-tuning LLMs has become much easier because of open-source tools. You no longer need to build the full training stack from scratch. Whether you want low-VRAM training, LoRA, QLoRA, RLHF, DPO, multi-GPU scaling, or a simple UI, there is likely a library that fits your workflow. Here are the best ...
Single Agent vs Multi-Agent: When to Build a Multi-Agent System
A practical guide to understanding AI agent design, ReAct workflows, and when to scale from a single agent to a multi-agent system.
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How to Build an Efficient Knowledge Base for AI Models
Building a knowledge base for AI models isn’t a one-time task but an iterative process of refinement.
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CSPNet Paper Walkthrough: Just Better, No Tradeoffs
A review of the Cross-Stage Partial Network paper — and a from-scratch PyTorch implementation
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Inference Scaling (Test-Time Compute): Why Reasoning Models Raise Your Compute Bill
Why reasoning models dramatically increase token usage, latency, and infrastructure costs in production systems
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Churn Without Fragmentation: How a Party-Label Bug Reversed My Headline Finding
A data quality case study from English local elections on categorical normalisation, metric validation, and why raw labels should never define analytical groups.
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Or why what appears powerful can be methodologically fragile
The post Why Powerful Machine Learning Is Deceptively Easy appeared first on Towards Data Science.
How to make decisions when your spreadsheet is lying about the future
The post A Gentle Introduction to Stochastic Programming appeared first on Towards Data Science.
How to Study the Monotonicity and Stability of Variables in a Scoring Model using Python
How can you validate that your variables tell a consistent risk?
The post How to Study the Monotonicity and Stability of Variables in a Scoring Model using Python appeared first on Towards Data Science.