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Explainable AI for PractitionersMost intermediate level machine learning books focus on how to optimize models increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does. Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best in class techniques for model explainability. Experienced

Cutting-room veterans have long maintained that visual juxtaposition fuels film storytelling

this introductory book provides a hands-on

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rapidly and painlessly

" -Times Literary Supplement "There's a growing market for savants who can render the recondite intelligibly-witness Stephen Jay Gould (natural history)

and have programming experience

proven practical methods for preventing and resolving the challenges faced todays hospitality practitioner

He is co-author of Software Architecture: The Hard Parts: Modern Trade-Off Analyses for Distributed Architectures

head off performance issues

C++ has come a long way and has now been adopted in several contexts

Use architectural design patterns such as model-view-controller to combine several OpenWhisk actions

technicians and those studying the subject below degree level

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