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Verlag: Taylor & Francis Ltd Nov 2024, 2024
ISBN 10: 1032136146 ISBN 13: 9781032136141
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware - This book emphasizes the idea of understanding the motivation of the advanced circuits' design to establish the AI interface and to mitigate the security attacks in a better way for big data. It is for students, researchers, and professionals, faculty members and software developers who wish to carry out further research.
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In den WarenkorbPaperback. Zustand: new. Paperback. Artificial intelligence (AI), machine learning, and advanced electronic circuits involve learning from every data input and using those inputs to generate new rules for future business analytics. AI and machine learning are now giving us new opportunities to use big data that we already had, as well as unleash a whole lot of new use cases with new data types. With the increasing use of AI dealing with highly sensitive information such as healthcare, adequate security measures are required to securely store and transmit this information. This book provides a broader coverage of the basic aspects of advanced circuits design and applications.AI for Big Data-Based Engineering Applications from Security Perspectives is an integrated source that aims at understanding the basic concepts associated with the security of advanced circuits. The content includes theoretical frameworks and recent empirical findings in the field to understand the associated principles, key challenges, and recent real-time applications of advanced circuits, AI, and big data security. It illustrates the notions, models, and terminologies that are widely used in the area of Very Large Scale Integration (VLSI) circuits, security, identifies the existing security issues in the field, and evaluates the underlying factors that influence system security. This work emphasizes the idea of understanding the motivation behind advanced circuit design to establish the AI interface and to mitigate security attacks in a better way for big data. This book also outlines exciting areas of future research where already existing methodologies can be implemented. This material is suitable for students, researchers, and professionals with research interest in AI for big databased engineering applications, faculty members across universities, and software developers. This book emphasizes the idea of understanding the motivation of the advanced circuits design to establish the AI interface and to mitigate the security attacks in a better way for big data. It is for students, researchers, and professionals, faculty members and software developers who wish to carry out further research. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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In den WarenkorbPaperback. Zustand: Brand New. 266 pages. 9.18x6.12x9.21 inches. In Stock.
Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032136146 ISBN 13: 9781032136141
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In den WarenkorbPaperback. Zustand: new. Paperback. Artificial intelligence (AI), machine learning, and advanced electronic circuits involve learning from every data input and using those inputs to generate new rules for future business analytics. AI and machine learning are now giving us new opportunities to use big data that we already had, as well as unleash a whole lot of new use cases with new data types. With the increasing use of AI dealing with highly sensitive information such as healthcare, adequate security measures are required to securely store and transmit this information. This book provides a broader coverage of the basic aspects of advanced circuits design and applications.AI for Big Data-Based Engineering Applications from Security Perspectives is an integrated source that aims at understanding the basic concepts associated with the security of advanced circuits. The content includes theoretical frameworks and recent empirical findings in the field to understand the associated principles, key challenges, and recent real-time applications of advanced circuits, AI, and big data security. It illustrates the notions, models, and terminologies that are widely used in the area of Very Large Scale Integration (VLSI) circuits, security, identifies the existing security issues in the field, and evaluates the underlying factors that influence system security. This work emphasizes the idea of understanding the motivation behind advanced circuit design to establish the AI interface and to mitigate security attacks in a better way for big data. This book also outlines exciting areas of future research where already existing methodologies can be implemented. This material is suitable for students, researchers, and professionals with research interest in AI for big databased engineering applications, faculty members across universities, and software developers. This book emphasizes the idea of understanding the motivation of the advanced circuits design to establish the AI interface and to mitigate the security attacks in a better way for big data. It is for students, researchers, and professionals, faculty members and software developers who wish to carry out further research. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032136146 ISBN 13: 9781032136141
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: new. Paperback. Artificial intelligence (AI), machine learning, and advanced electronic circuits involve learning from every data input and using those inputs to generate new rules for future business analytics. AI and machine learning are now giving us new opportunities to use big data that we already had, as well as unleash a whole lot of new use cases with new data types. With the increasing use of AI dealing with highly sensitive information such as healthcare, adequate security measures are required to securely store and transmit this information. This book provides a broader coverage of the basic aspects of advanced circuits design and applications.AI for Big Data-Based Engineering Applications from Security Perspectives is an integrated source that aims at understanding the basic concepts associated with the security of advanced circuits. The content includes theoretical frameworks and recent empirical findings in the field to understand the associated principles, key challenges, and recent real-time applications of advanced circuits, AI, and big data security. It illustrates the notions, models, and terminologies that are widely used in the area of Very Large Scale Integration (VLSI) circuits, security, identifies the existing security issues in the field, and evaluates the underlying factors that influence system security. This work emphasizes the idea of understanding the motivation behind advanced circuit design to establish the AI interface and to mitigate security attacks in a better way for big data. This book also outlines exciting areas of future research where already existing methodologies can be implemented. This material is suitable for students, researchers, and professionals with research interest in AI for big databased engineering applications, faculty members across universities, and software developers. This book emphasizes the idea of understanding the motivation of the advanced circuits design to establish the AI interface and to mitigate the security attacks in a better way for big data. It is for students, researchers, and professionals, faculty members and software developers who wish to carry out further research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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ISBN 10: 7308247791 ISBN 13: 9787308247795
Sprache: Englisch
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In den Warenkorbpaperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2024-04 Publisher: Zhejiang University Press This book introduces the application of statistical methods in data analysis through application cases and with the help of R software. Main contents: data representation and visualization. linear regression analysis. stepwise regression and regression diagnosis. generalized linear model and nonlinear model. variance analysis. cluster analysis. discriminant analysis. principal component analysis. factor analysi.
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