Engineering Dependable And Secure Machine Learning Systems

DOWNLOAD

Download Engineering Dependable And Secure Machine Learning Systems PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Engineering Dependable And Secure Machine Learning Systems book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Engineering Dependable And Secure Machine Learning Systems

DOWNLOAD
Author : Onn Shehory
language : en
Publisher: Springer Nature
Release Date : 2020-11-07

Engineering Dependable And Secure Machine Learning Systems written by Onn Shehory and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-07 with Computers categories.

This book constitutes the revised selected papers of the Third International Workshop on Engineering Dependable and Secure Machine Learning Systems, EDSMLS 2020, held in New York City, NY, USA, in February 2020. The 7 full papers and 3 short papers were thoroughly reviewed and selected from 16 submissions. The volume presents original research on dependability and quality assurance of ML software systems, adversarial attacks on ML software systems, adversarial ML and software engineering, etc.

Beyond Algorithms

DOWNLOAD
Author : James Luke
language : en
Publisher: CRC Press
Release Date : 2022-05-29

Beyond Algorithms written by James Luke and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-29 with Computers categories.

With so much artificial intelligence (AI) in the headlines, it is no surprise that businesses are scrambling to exploit this exciting and transformative technology. Clearly, those who are the first to deliver business-relevant AI will gain significant advantage. However, there is a problem! Our perception of AI success in society is primarily based on our experiences with consumer applications from the big web companies. The adoption of AI in the enterprise has been slow due to various challenges. Business applications address far more complex problems and the data needed to address them is less plentiful. There is also the critical need for alignment of AI with relevant business processes. In addition, the use of AI requires new engineering practices for application maintenance and trust. So, how do you deliver working AI applications in the enterprise? Beyond Algorithms: Delivering AI for Business answers this question. Written by three engineers with decades of experience in AI (and all the scars that come with that), this book explains what it takes to define, manage, engineer, and deliver end-to-end AI applications that work. This book presents: Core conceptual differences between AI and traditional business applications A new methodology that helps to prioritise AI projects and manage risks Practical case studies and examples with a focus on business impact and solution delivery Technical Deep Dives and Thought Experiments designed to challenge your brain and destroy your weekends

Deep Learning For Multi Sensor Earth Observation

DOWNLOAD
Author : Sudipan Saha
language : en
Publisher: Elsevier
Release Date : 2025-02-03

Deep Learning For Multi Sensor Earth Observation written by Sudipan Saha and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-03 with Technology & Engineering categories.

Deep Learning for Multi-Sensor Earth Observation addresses the need for transformative Deep Learning techniques to navigate the complexity of multi-sensor data fusion. With insights drawn from the frontiers of remote sensing technology and AI advancements, it covers the potential of fusing data of varying spatial, spectral, and temporal dimensions from both active and passive sensors. This book offers a concise, yet comprehensive, resource, addressing the challenges of data integration and uncertainty quantification from foundational concepts to advanced applications. Case studies illustrate the practicality of deep learning techniques, while cutting-edge approaches such as self-supervised learning, graph neural networks, and foundation models chart a course for future development.Structured for clarity, the book builds upon its own concepts, leading readers through introductory explanations, sensor-specific insights, and ultimately to advanced concepts and specialized applications. By bridging the gap between theory and practice, this volume equips researchers, geoscientists, and enthusiasts with the knowledge to reshape Earth observation through the dynamic lens of deep learning. - Addresses the problem of unwieldy datasets from multi-sensor observations, applying Deep Learning to multi-sensor data integration from disparate sources with different resolution and quality - Provides a thorough foundational reference to Deep Learning applications for handling Earth Observation multi-sensor data across a variety of geosciences - Includes case studies and real-world data/examples allowing readers to better grasp how to put Deep Learning techniques and methods into practice

Neural Information Processing

DOWNLOAD
Author : Mufti Mahmud
language : en
Publisher: Springer Nature
Release Date : 2025-08-19

Neural Information Processing written by Mufti Mahmud and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-19 with Computers categories.

The sixteen-volume set, CCIS 2282-2297, constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024. The 472 regular papers presented in this proceedings set were carefully reviewed and selected from 1301 submissions. These papers primarily focus on the following areas: Theory and algorithms; Cognitive neurosciences; Human-centered computing; and Applications.

Computational Science Iccs 2019

DOWNLOAD
Author : João M. F. Rodrigues
language : en
Publisher: Springer
Release Date : 2019-06-07

Computational Science Iccs 2019 written by João M. F. Rodrigues and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-07 with Computers categories.

The five-volume set LNCS 11536, 11537, 11538, 11539 and 11540 constitutes the proceedings of the 19th International Conference on Computational Science, ICCS 2019, held in Faro, Portugal, in June 2019. The total of 65 full papers and 168 workshop papers presented in this book set were carefully reviewed and selected from 573 submissions (228 submissions to the main track and 345 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track; Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Matrix Methods in Artificial Intelligence and Machine Learning; Track of Architecture, Languages, Compilation and Hardware Support for Emerging and Heterogeneous Systems Part III: Track of Biomedical and Bioinformatics Challenges for Computer Science; Track of Classifier Learning from Difficult Data; Track of Computational Finance and Business Intelligence; Track of Computational Optimization, Modelling and Simulation; Track of Computational Science in IoT and Smart Systems Part IV: Track of Data-Driven Computational Sciences; Track of Machine Learning and Data Assimilation for Dynamical Systems; Track of Marine Computing in the Interconnected World for the Benefit of the Society; Track of Multiscale Modelling and Simulation; Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation Part V: Track of Smart Systems: Computer Vision, Sensor Networks and Machine Learning; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Poster Track ICCS 2019 Chapter “Comparing Domain-decomposition Methods for the Parallelization of Distributed Land Surface Models” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Reliable Machine Learning

DOWNLOAD
Author : Cathy Chen
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-10-12

Reliable Machine Learning written by Cathy Chen and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-12 with Computers categories.

Whether you're part of a small startup or a multinational corporation, this practical book shows data scientists, software and site reliability engineers, product managers, and business owners how to run and establish ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization. By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guest authors show you how to run an efficient and reliable ML system. Whether you want to increase revenue, optimize decision making, solve problems, or understand and influence customer behavior, you'll learn how to perform day-to-day ML tasks while keeping the bigger picture in mind. You'll examine: What ML is: how it functions and what it relies on Conceptual frameworks for understanding how ML "loops" work How effective productionization can make your ML systems easily monitorable, deployable, and operable Why ML systems make production troubleshooting more difficult, and how to compensate accordingly How ML, product, and production teams can communicate effectively

2008 37th International Conference On Parallel Processing

DOWNLOAD
Author : IEEE Staff
language : en
Publisher:
Release Date : 2008

2008 37th International Conference On Parallel Processing written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Technology & Engineering categories.

Publications Bulletin

DOWNLOAD
Author : European Commission. Joint Research Centre
language : en
Publisher:
Release Date : 2000

Publications Bulletin written by European Commission. Joint Research Centre and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Research categories.

Japanese Technical Periodical Index

DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1987

Japanese Technical Periodical Index written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Engineering categories.

Science International

DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1999

Science International written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Science categories.