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Designing autonomous ai: a guide for machine teaching, kence anderson

730 грн

Описание

Early rules-based artificial intelligence demonstrated intriguing decision-
making capabilities but lacked perception and didn't learn. AI today, primed
with machine learning perception and deep reinforcement learning capabilities,
can perform superhuman decision-making for specific tasks. This book shows you
how to combine the practicality of early AI with deep learning capabilities
and industrial control technologies to make robust decisions in the real
world. \n \nUsing concrete examples, minimal theory, and a proven
architectural framework, author Kence Anderson demonstrates how to teach
autonomous AI explicit skills and strategies. You'll learn when and how to use
and combine various AI architecture design patterns, as well as how to design
advanced AI without needing to manipulate neural networks or machine learning
algorithms. Students, process operators, data scientists, machine learning
algorithm experts, and engineers who own and manage industrial processes can
use the methodology in this book to design autonomous AI. \n \nThis book
examines: \n

- Differences between and limitations of automated, autonomous, and human decision-making
\n

- Unique advantages of autonomous AI for real-time decision-making, with use cases
\n

- How to design an autonomous AI from modular components and document your designs
\n

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