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The Architecture of AI: Understanding the Building Blocks of Machine Intelligence. MACHINE INTELLIGENCE

Par : Elizabeth Mogopodi
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  • FormatePub
  • ISBN8232449568
  • EAN9798232449568
  • Date de parution17/11/2025
  • Protection num.pas de protection
  • Infos supplémentairesepub
  • ÉditeurHamza elmir

Résumé

"The Architecture of AI: Understanding the Building Blocks of Machine Intelligence" is a comprehensive guide that explores the foundational principles and key components of artificial intelligence. This book provides a thorough understanding of AI architecture, covering the essential concepts, technologies, and methodologies that underpin intelligent systems. Through a detailed examination of data, models, algorithms, and infrastructure, readers will gain a deep understanding of how AI systems are designed, developed, and deployed.
With a focus on practicality and applicability, this book is ideal for anyone looking to build a strong foundation in AI, including students, professionals, and researchers. Key topics include:- Fundamentals of AI and machine learning- Data preprocessing and feature engineering- Model development and evaluation- AI algorithms and architectures- Infrastructure and deployment considerations- Ethics and governance in AI By reading this book, readers will gain a comprehensive understanding of the building blocks of machine intelligence and be equipped with the knowledge and skills to design, develop, and deploy effective AI solutions.
"The Architecture of AI: Understanding the Building Blocks of Machine Intelligence" is a comprehensive guide that explores the foundational principles and key components of artificial intelligence. This book provides a thorough understanding of AI architecture, covering the essential concepts, technologies, and methodologies that underpin intelligent systems. Through a detailed examination of data, models, algorithms, and infrastructure, readers will gain a deep understanding of how AI systems are designed, developed, and deployed.
With a focus on practicality and applicability, this book is ideal for anyone looking to build a strong foundation in AI, including students, professionals, and researchers. Key topics include:- Fundamentals of AI and machine learning- Data preprocessing and feature engineering- Model development and evaluation- AI algorithms and architectures- Infrastructure and deployment considerations- Ethics and governance in AI By reading this book, readers will gain a comprehensive understanding of the building blocks of machine intelligence and be equipped with the knowledge and skills to design, develop, and deploy effective AI solutions.