Zhu xiwei (60 risultati)

Soft cover. Condizione: New. ISBN:9789361592874,Territorial restriction maybe printed on the book. This is an Int'l edition, ISBN and cover may differ from US edition, Contents same as US edition.

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Paperback. Condizione: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Paperback. Condizione: New. 1st. AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies. Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover: Governance mechanisms at industry, organisation, and team levelsDevelopment process perspectives, including software engineering best practices for AISystem perspectives, including quality attributes, architecture styles, and patternsTechniques for connecting code with data and models, including key tradeoffsPrinciple-specific techniques for fairness, privacy, and explainabilityA preview of the future of responsible AI.…

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Condizione: New. In English.

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Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

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Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

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Condizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.

Paperback. Condizione: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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Paperback. Condizione: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability. …

Paperback. Condizione: Brand New. 320 pages. 9.06x7.36x0.71 inches. In Stock.

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Condizione: New. &Uumlber den AutorDr. Qinghua Lu is a principal research scientist and leads the Responsible AI science team at CSIROs Data61. She received her PhD from University of New South Wales in 2013. Her current research int.

Condizione: New. 448.

Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

Paperback. Condizione: New. 1st. AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies. Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover: Governance mechanisms at industry, organisation, and team levelsDevelopment process perspectives, including software engineering best practices for AISystem perspectives, including quality attributes, architecture styles, and patternsTechniques for connecting code with data and models, including key tradeoffsPrinciple-specific techniques for fairness, privacy, and explainabilityA preview of the future of responsible AI.…