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Explainable AI

Making Machine Intelligence Transparent, Trustworthy, and Understandable for Human Decision-Making

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Explainable AI

By: Sam Miley
Narrated by: Maha Amir
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About this listen

Build AI systems that don’t just work — they win trust.

In today’s fast-moving AI-powered world, accuracy isn’t enough. Whether you’re building models for healthcare, finance, retail, or enterprise software, one thing is clear: if users and stakeholders can’t understand your AI, they won’t trust it.

Explainable AI is your practical, results-driven guide to building transparent, trustworthy, and human-friendly AI systems. Packed with real-world examples and proven techniques, this book shows you how to turn black-box models into clear, interpretable tools that users can believe in—and regulators can approve.

What you’ll gain from this book:

  • Tools like SHAP and LIME to explain predictions clearly
  • Strategies to increase model transparency without sacrificing accuracy
  • Step-by-step ways to meet compliance, reduce risk, and gain user buy-in
  • Industry case studies that prove explainability is a competitive advantage

Insights that make your AI smarter and more responsible

If you want to build AI solutions that people trust, adopt, and love—this is the book that will show you how.

©2025 Sam Miley (P)2025 Sam Miley
Computer Science Machine Theory & Artificial Intelligence
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