How to Implement Structured Output with Local LLMs
Why use it? How to implement it?
The article "How to Fine-Tune an LLM: An End-to-End Guide" offers a practical, hands‑on walkthrough for fine‑tuning large language models in real‑world scenarios. It covers the entire process from data preparation to deployment, providing readers with actionable steps to adapt LLMs to specific tasks. The guide is aimed at practitioners looking to implement fine‑tuning in a structured, end‑to‑end manner.
Why use it? How to implement it?
Getting reliable, readable responses out of your LLM, and knowing which tool to reach for The post Structured Outputs with LLMs: JSON Mode, Function Calling, and When to Use Each appeared first on Towards Data Science .
Increase productivity with your LLMs The post How to Effectively Align with Claude Code appeared first on Towards Data Science .
Use coding agents to power your knowledge base The post How to Build a Powerful LLM Knowledge Base appeared first on Towards Data Science .
Two techniques, two different problems, and why the question is not really "which one wins" The post RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each appeared first on Towards Data Science .
Become a more productive software engineer with LLMs The post How to Perform Effective Project Management with AI appeared first on Towards Data Science .
Enterprise Document Intelligence [Vol. 1 #8quater] - Two angles on the cascade, cost and a validation loop, backed by a real sweep of twenty local models against a hosted flagship The post Loop Engineering for RAG Generation: An LLM Cascade from a Cheap Local Model Up to a Hosted Flagship appeared first on Towards Data Science .
The idea that makes backpropagation possible. The post Backpropagation Explained for Beginners (Part 2): There Has to Be a Better Way appeared first on Towards Data Science .
The article titled "How to Effectively Align Your Intent with Claude Code" discusses strategies for improving proficiency with Claude Code. It offers guidance on how to align your intentions with the code to achieve better results. The post was originally published on Towards Data Science.
This is how LLMs are used today to increase precision in recommendation systems The post Increase Recommendation Systems’ Precision with LLMs, Using Python appeared first on Towards Data Science .
Understanding ow LLMs interact with the world around them, from returning data to taking action The post Tool Calling, Explained: How AI Agents Decide What to Do Next appeared first on Towards Data Science .
A reflection on the first month of learning data engineering in public, and what actually kept me going. The post One Month Into Learning Data Engineering in Public: Here’s What I Didn’t Write About appeared first on Towards Data Science .