My AI Couldn’t See My Files — I Built a Zero-Dependency MCP Server
I got tired of copying files into an AI chat just to get feedback. So I built a pure Python MCP server that gives AI tools direct access to my local project—no frameworks, no dependencies. It runs over stdio for local use and switches to HTTP/SSE for concurrent clients with a single flag. The result...
Using DSPy to automatically create, evaluate, and optimize your prompts
The post Automate Writing Your LLM Prompts appeared first on Towards Data Science.
3 SpaCy Tricks for Efficient Text Processing & Entity Recognition
In this article, we will explore three essential spaCy tricks that every developer should have in their toolkit to maximize processing speed and customize entity recognition.
Five Ways to Fine-Tune Chronos-2, the Time Series Foundation Model
In Part 1 of this series, we introduced Chronos-2, a time-series foundation model. We got our hands dirty by walking through a real case study and saw what Chronos-2 can do straight out of the box, with no training. But as we noted at the end of Part 1, zero-shot isn’t always enough. In cases […]
Th...
Small Data, Big Maps: Training Geospatial ML Models When Samples Are Scarce
When images, mosaics, and data cubes exist in abundance, but field labels are expensive, rare, and imperfect.
The post Small Data, Big Maps: Training Geospatial ML Models When Samples Are Scarce appeared first on Towards Data Science.
FPN Paper Walkthrough: Leveraging the Internal Pyramid
Understanding how FPN allows deep learning models detecting small objects and how to implement it from scratch
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This article will teach you how to perform a language task like text classification by integrating locally hosted large language models (LLMs) of manageable size, like Mistral, Gemma, and Llama 3: all for free thanks to Ollama — a free repository for local LLMs — and the Scikit-LLM Python library.
Agent Observability with LangSmith, Langfuse, and Arize: A Hands-On Comparison
Your AI agent works great in testing. Then you ship it, and something kinda breaks. A tool called loops forever, like it never learns. A retrieval step returns garbage and costs spike. You have no idea why, at all. That’s the agent observability problem. And if you’re building with LLMs, you need to...
I Built a C++ Backend So My GPU Would Stop Eating Air
A comprehensive guide to optimizing LLM inference by eliminating padding overhead with hardware-aware sequence packing.
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How to set the rules that keep agents effective and out of trouble
The post What AI Agents Should Never Do on Their Own appeared first on Towards Data Science.
Code Is Cheap. Engineering Judgement Is Now the Scarce Resource
The barriers to building have collapsed. That shifts the bottleneck to ownership, validation, taste, and deciding what should actually exist
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Three free ways to quickly deploy a static web app that anyone can access
The post From Local App to Public Website in Minutes appeared first on Towards Data Science.
From Regex to Vision Models: Which RAG Technique Fits Which Problem
Enterprise Document Intelligence [Vol.1 #4] - A diagnostic across PDFs and questions, and a map of the techniques the rest of the series will cover
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10 GitHub Repositories for Modern Database Systems and Tools
Explore 10 top open-source GitHub repositories for modern databases, analytics, SQL, caching, monitoring, replication, PostgreSQL, SQLite, and AI agent memory.
RAG Is Not Machine Learning, and the ML Toolkit Solves the Wrong Problem
Enterprise Document Intelligence [Vol.1 #3] - Why the ML toolkit (hyperparameter sweeps, train/test splits, explainability frameworks) solves the wrong problem, and what to use instead
The post RAG Is Not Machine Learning, and the ML Toolkit Solves the Wrong Problem appeared first on Towards Data Sc...
Mocking a Year of IoT Sensor Time Series Data with Mimesis
In this guide, you will learn the process of generating a year's worth of daily temperature readings, mimicking a seasonal curve that looks like real — all together with device-level metadata, and ready to build based on open-source frameworks.