Kniha Beyond the Hype Ryan Mercer

Beyond the Hype

A Practical Guide to AI and Machine Learning for the Real World | The No-Hype Guide to How AI Really Works | Cut Through the Noise and Understand What AI Can Actually Do

Autor: Ryan Mercer
Jazyk: Angličtina
Väzba: Brožovaná
Dostupnosť: Skladom u dodávateľa
Odosielame za 14-21 dní
9.52
Everyone is talking about AI. Almost no one can tell you, clearly and honestly, what it actually doe...

Informácie o knihe

Autor
Jazyk
Angličtina
Väzba
Kniha - Brožovaná
Vydalo
2026
Stránok
74
EAN
9798187957989
Enbook ID
53269233
Hmotnosť
113
Rozmery
152 x 229 x 4

Kompletný popis

Everyone is talking about AI. Almost no one can tell you, clearly and honestly, what it actually does.

Artificial intelligence has become the most overused word in modern language, stretched to cover everything from a spreadsheet formula to speculative super intelligence. Beyond the Hype cuts through that noise with a clear, jargon-free guide to how AI and machine learning actually work, what they can realistically do, and where the hype quietly outruns the substance.

You don't need a background in coding, math, or statistics to read this book. Every concept is explained in plain English first, from neural networks and large language models to computer vision and generative AI, with technical detail introduced only as far as it helps you think clearly about the technology.

What makes this book different

Every chapter ends with two short, practical sections:

  • Reality Check - a common AI myth, and the honest truth behind it
  • Practice Drill - a five-minute hands-on exercise, no coding required

    No hype. No fear-mongering. Just a clear-eyed look at a technology that is genuinely reshaping the world, minus the marketing.

    Inside, you'll learn:
    • What AI, machine learning, and deep learning actually mean, and how they relate
    • How machines "learn" from data, and why that's different from human understanding
    • Supervised, unsupervised, and reinforcement learning, explained simply
    • How neural networks, transformers, and large language models really work
    • Why AI "hallucinates," and how to spot it
    • Where computer vision and generative AI succeed, and where they quietly fail
    • How to evaluate whether an AI model is actually good, not just impressive-looking
    • The real ethical questions around bias, privacy, and accountability
    • How businesses actually succeed, and mostly fail, at implementing AI
    • Where the field is headed, without hype or panic in either direction

    Whether you're a professional trying to make sense of AI's impact on your industry, a student building a foundation before deeper technical study, a manager evaluating a vendor's pitch, or simply someone who wants to separate signal from noise, this book was written for you.

    Stop reading AI headlines you can't evaluate. Start understanding what's actually happening.

    Includes a full glossary of AI and machine learning terms for quick reference.