Artificial Intelligence : A Systems Approach from Architecture Principles to Deployment
Book Details
Format
Hardback or Cased Book
ISBN-10
0262048981
ISBN-13
9780262048989
Publisher
MIT Press Ltd
Imprint
MIT Press
Country of Manufacture
US
Country of Publication
GB
Publication Date
Jun 11th, 2024
Print length
576 Pages
Weight
1,226 grams
Dimensions
23.50 x 18.60 x 4.50 cms
Product Classification:
Information technology: general issues
Ksh 18,900.00
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The first text to take a systems engineering approach to artificial intelligence (AI), from architecture principles to the development and deployment of AI capabilities.
Most books on artificial intelligence (AI) focus on a single functional building block, such as machine learning or human-machine teaming. Artificial Intelligence takes a more holistic approach, addressing AI from the view of systems engineering. The book centers on the people-process-technology triad that is critical to successful development of AI products and services. Development starts with an AI design, based on the AI system architecture, and culminates with successful deployment of the AI capabilities. Directed toward AI developers and operational users, this accessibly written volume of the MIT Lincoln Laboratory Series can also serve as a text for undergraduate seniors and graduate-level students and as a reference book.
Key features:
Most books on artificial intelligence (AI) focus on a single functional building block, such as machine learning or human-machine teaming. Artificial Intelligence takes a more holistic approach, addressing AI from the view of systems engineering. The book centers on the people-process-technology triad that is critical to successful development of AI products and services. Development starts with an AI design, based on the AI system architecture, and culminates with successful deployment of the AI capabilities. Directed toward AI developers and operational users, this accessibly written volume of the MIT Lincoln Laboratory Series can also serve as a text for undergraduate seniors and graduate-level students and as a reference book.
Key features:
- In-depth look at modern computing technologies
- Systems engineering description and means to successfully undertake an AI product or service development through deployment
- Existing methods for applying machine learning operations (MLOps)
- AI system architecture including a description of each of the AI pipeline building blocks
- Challenges and approaches to attend to responsible AI in practice
- Tools to develop a strategic roadmap and techniques to foster an innovative team environment
- Multiple use cases that stem from the authors MIT classes, as well as from AI practitioners, AI project managers, early-career AI team leaders, technical executives, and entrepreneurs
- Exercises and Jupyter notebook examples
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