The Pocketbook of Artificial Intelligence Terminology: A Practical Glossary for AI, Machine Learning, LLMs, RAG, Agents, Python, and AI Engineering

Artificial intelligence has its own language, and for a lot of people, that language can feel like the first real barrier to understanding the field.The Pocketbook of Artificial Intelligence Terminology was written to make that barrier easier to get past.This book is a practical, plain-English glossary for the words, tools, concepts, and technical ideas that show up across modern AI. It covers artificial intelligence, machine learning, large language models, retrieval-augmented generation, agentic AI, Python development, embeddings, vector databases, model evaluation, deployment, and the growing stack of tools used by AI developers and engineers.Instead of giving you short, lifeless dictionary definitions, this book explains each term in a clear and useful way. The goal is not just to tell you what a word means, but to help you understand why it matters and where it fits in the larger AI ecosystem.Inside, you will find explanations for terms such as: AI agents, agentic workflows, embeddings, vector databases, RAG, LangChain, LangGraph, ChromaDB, hallucination, prompt engineering, context windows, fine-tuning, transformers, retrieval, reranking, model evaluation, LLM-as-judge, Python, APIs, neural networks, supervised learning, reinforcement learning, and many more.This book is designed for: Students learning AI terminology for the first timeDevelopers and engineers moving into AIBusiness professionals trying to understand AI products and technical discussionsWriters, creators, and researchers who want a clearer grasp of AI languageSelf-taught builders working with Python, LLMs, RAG, and AI toolsAnyone tired of hearing AI terms explained in a way that creates more confusion than clarityThe Pocketbook of Artificial Intelligence Terminology is not meant to be an academic textbook or a hype-filled overview of AI. It is meant to be a useful reference you can keep nearby while reading documentation, watching tutorials, building projects, taking courses, or trying to understand what people actually mean when they talk about modern AI.If you want a clearer, more practical understanding of the language behind artificial intelligence, this book is a strong place to start.

Pagina's: 183, Paperback, Independently published