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Explainable AI

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

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Explainable AI

Auteur(s): Sam Miley
Narrateur(s): Maha Ameer
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À propos de cet audio

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.

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