How to Train an LLM

A Practical Guide for Developers, Data Scientists, and Indie AI Builders

De: Trent Farrens

Narrado por: Virtual Voice

“How to Train an LLM” is a practical, end-to-end guide to building and tuning language models for real-world use. Written for hands-on practitioners, it walks developers, data scientists, and indie AI builders through the entire lifecycle: from curating datasets and choosing architectures to fine-tuning, evaluating, and deploying models into production.

Instead of hand‑wavy theory, this book focuses on the decisions that actually matter: what data you really need, how to structure training runs, how to avoid common failure modes like overfitting and hallucinations, and how to monitor and iterate after launch. You’ll learn how to leverage open‑source models, work within real hardware and budget constraints, and design practical workflows that let small teams punch far above their weight.

Whether you’re a software engineer stepping into machine learning, a data scientist moving into large‑scale NLP, or an indie founder building your first AI‑powered product, this book gives you the mental models, checklists, and patterns you need to train LLMs that are robust, useful, and shippable.