[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_28":-5,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":56,"_57":58},"routes/_store+/_readers+/email_author.$slug/route",{"_9":10,"_11":-5},"book",{"_12":13,"_14":15,"_16":17,"_18":19,"_20":21,"_22":23},"currentUser","id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvODA5MDg","title","AI Without Mathematics","state","published","contactAuthorMethod","email","aboutText","

AI Without Mathematics is a practical guide to understanding modern AI systems without getting blocked by equations on day one.

A lot of AI learning resources have one of two problems: they either become too abstract too early, throwing readers into notation and theory before they understand what the systems are doing, or they stay too shallow, explaining buzzwords and demos without building a real mental model of how modern AI applications fit together.

This book was written to sit in the middle.

It explains the major building blocks of modern AI in plain language and from a systems-first perspective. Instead of starting with heavy math, it helps you understand what each component is for, what problem it solves, and how it fits into real AI applications.

Inside the book, you’ll learn about:

AI, machine learning, deep learning, and neural networks
how LLMs generate text and why tokens, context windows, and attention matter
embeddings, vector search, and vector databases
how RAG systems work end to end
when GraphRAG is useful and when it isn’t
agents, tools, workflows, and memory in AI systems
evaluation, guardrails, and reliability
what fine-tuning is actually for, and when it is the wrong solution
inference speed, decoding, latency, and optimization tradeoffs
how to think about building practical AI projects rather than just learning isolated terms

This book is for students, developers, and builders who want to move beyond AI buzzwords and build a clear mental model of how modern AI systems actually work.

You do not need advanced mathematics to read it.

If you want a practical introduction to LLMs, retrieval, RAG, agents, GraphRAG, evaluation, and AI engineering concepts — without starting from equations — this book is for you.

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Kick off your book project, get started with GhostAI, get better at marketing, or spend the day doing all three! Free live workshops on Zoom. Saturday, June 27, 2026.

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