Data Science in Engineering, Volume 10

Data Science in Engineering, Volume 10 PDF

Author: Ramin Madarshahian

Publisher: Springer Nature

Published: 2023-12-07

Total Pages: 185

ISBN-13: 3031349466

DOWNLOAD EBOOK →

Data Science in Engineering, Volume 10: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the tenth volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Novel Data-driven Analysis Methods Deep Learning Gaussian Process Analysis Real-time Video-based Analysis Applications to Nonlinear Dynamics and Damage Detection High-rate Structural Monitoring and Prognostics

Data-Driven Science and Engineering

Data-Driven Science and Engineering PDF

Author: Steven L. Brunton

Publisher: Cambridge University Press

Published: 2022-05-05

Total Pages: 615

ISBN-13: 1009098489

DOWNLOAD EBOOK →

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Data Engineering and Data Science

Data Engineering and Data Science PDF

Author: Kukatlapalli Pradeep Kumar

Publisher: John Wiley & Sons

Published: 2023-08-29

Total Pages: 367

ISBN-13: 1119841976

DOWNLOAD EBOOK →

DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

Data Science in Engineering, Volume 9

Data Science in Engineering, Volume 9 PDF

Author: Ramin Madarshahian

Publisher: Springer Nature

Published: 2021-10-04

Total Pages: 287

ISBN-13: 3030760049

DOWNLOAD EBOOK →

Data Science and Engineering Volume 9: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021, the ninth volume of nine from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Data Science in Engineering Applications Engineering Mathematics Computational Methods in Engineering

Data Science in Engineering and Management

Data Science in Engineering and Management PDF

Author: Zdzislaw Polkowski

Publisher: CRC Press

Published: 2021-12-31

Total Pages: 159

ISBN-13: 1000520846

DOWNLOAD EBOOK →

This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis. Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively. This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

Foundations of Data Science for Engineering Problem Solving

Foundations of Data Science for Engineering Problem Solving PDF

Author: Parikshit Narendra Mahalle

Publisher: Springer Nature

Published: 2021-08-21

Total Pages: 125

ISBN-13: 9811651604

DOWNLOAD EBOOK →

This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.

Foundations of Data Science

Foundations of Data Science PDF

Author: Avrim Blum

Publisher: Cambridge University Press

Published: 2020-01-23

Total Pages: 433

ISBN-13: 1108617360

DOWNLOAD EBOOK →

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.

Reviews Of Accelerator Science And Technology - Volume 10: The Future Of Accelerators

Reviews Of Accelerator Science And Technology - Volume 10: The Future Of Accelerators PDF

Author: Chao Alexander Wu

Publisher: World Scientific

Published: 2019-09-09

Total Pages: 352

ISBN-13: 9811209618

DOWNLOAD EBOOK →

Volume 10 in the series of the annual journal Reviews of Accelerator Science and Technology (RAST), will be its final volume. Its theme is 'The Future of Accelerators'. This volume, together with previous 9 volumes, gives readers a complete picture as well as detailed technical information about the accelerator field, and its many driving and fascinating aspects.This volume has 17 articles. The first 15 articles have a different approach from the previous volumes. They emphasize the more personal views, perspectives and advice from the frontier researchers rather than provide a review or survey of a specific subfield. This emphasis is more aligned with the theme of the current volume. The other two articles are dedicated respectively to Leon Lederman and Burton Richter, two prominent leaders of our community who left us last year.

Proceedings of the International Conference on Information Engineering, Management and Security 2015

Proceedings of the International Conference on Information Engineering, Management and Security 2015 PDF

Author: Vignesh Ramakrishnan

Publisher: Association of Scientists, Developers and Faculties (ASDF)

Published: 2015-08-13

Total Pages: 342

ISBN-13: 8192974278

DOWNLOAD EBOOK →

ICIEMS 2015 is the conference aim is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results and development activities in Engineering Technology, Industrial Engineering, Application Level Security and Management Science. This conference provides opportunities for the delegates to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration.

Integrated Business Models in the Digital Age

Integrated Business Models in the Digital Age PDF

Author: Sumesh Singh Dadwal

Publisher: Springer Nature

Published: 2022-06-21

Total Pages: 574

ISBN-13: 303097877X

DOWNLOAD EBOOK →

Many scholars have argued that technology, entrepreneurship, integrated business models and marketing are key to the success of any business, but in particular to the success of unicorn companies. However, there is a need to further investigate interdisciplinary approaches to techno entrepreneurial business strategy, which remains a neglected area of research. In this edited volume, authors explore and develop principles, models and other theoretical and practical concepts to develop better guidance on how to adapt business models using new technologies such as AI, cloud computing, blockchain, cybersecurity, and infrastructure. Underpinned by established academic theories, the book explores integrated business models that are both defensive and offensive in strategic outlook. Ultimately, it will help students, researchers and entrepreneurs to design, develop and implement technology-enabled integrated business models.