NeuroSymbolic Artificial Intelligence Second Edition (Paperback)

Gareth Morgan Thomas

ISBN 13: 9798308620761

Published by Independently Published, 2025

About this Item

Paperback. A Collection of Explorations in Code and ThoughtNot your typical textbook. Not a structured guide. This is a deep dive into the tangled web of logic, algorithms, and modern AI-told in code, mathematics, and mild discussion.In this book, you'll find an eclectic mix of ideas at the intersection of symbolic reasoning and neural networks. The content isn't designed for a classroom. It's a mashup of notes, insights, and raw explorations, written for those who enjoy jumping between theory and implementation without a rigid roadmap.What's Inside?Code samples in Node.js, Prolog, LISP, Python, Go, Rust, and Julia.Mathematical reasoning that underpins AI and computational logic.A mild but thought-provoking discussion on concepts ranging from symbolic AI to deep learning.No hand-holding, no introductions-just direct engagement with the material.This book is for tinkerers, AI researchers, and programmers who prefer to explore at their own pace. If you enjoy skimming code, unraveling logic puzzles, and seeing AI concepts unfold without an academic filter, this book belongs on your shelf.If you're looking for a structured AI textbook, this isn't it. But if you thrive on the raw, unpolished beauty of AI's evolution-welcome. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9798308620761

Bibliographic Details

• Title: NeuroSymbolic Artificial Intelligence Second Edition (Paperback)
• Publisher: Independently Published
• Publication Date: 2025
• Language: English
• ISBN 13: 9798308620761
• Binding: Paperback
• Condition: new

About this title

Synopsis

A Collection of Explorations in Code and Thought

Not your typical textbook. Not a structured guide. This is a deep dive into the tangled web of logic, algorithms, and modern AI—told in code, mathematics, and mild discussion.

In this book, you’ll find an eclectic mix of ideas at the intersection of symbolic reasoning and neural networks. The content isn’t designed for a classroom. It’s a mashup of notes, insights, and raw explorations, written for those who enjoy jumping between theory and implementation without a rigid roadmap.

What’s Inside?

• Code samples in Node.js, Prolog, LISP, Python, Go, Rust, and Julia.
• Mathematical reasoning that underpins AI and computational logic.
• A mild but thought-provoking discussion on concepts ranging from symbolic AI to deep learning.
• No hand-holding, no introductions—just direct engagement with the material.

This book is for tinkerers, AI researchers, and programmers who prefer to explore at their own pace. If you enjoy skimming code, unraveling logic puzzles, and seeing AI concepts unfold without an academic filter, this book belongs on your shelf.

If you’re looking for a structured AI textbook, this isn’t it. But if you thrive on the raw, unpolished beauty of AI’s evolution—welcome.