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Advanced Data Science and Analytics with Python (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

by Jesus Rogel-Salazar

Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. Features: Targets readers with a background in programming, who are interested in the tools used in data analytics and data science Uses Python throughout Presents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs Focuses on the practical use of the tools rather than on lengthy explanations Provides the reader with the opportunity to use the book whenever needed rather than following a sequential path The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others, providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered. The book discusses the need to develop data products and addresses the subject of bringing models to their intended audiences – in this case, literally to the users’ fingertips in the form of an iPhone app. About the Author Dr. Jesús Rogel-Salazar is a lead data scientist in the field, working for companies such as Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.

Advanced Data Mining and Applications: 14th International Conference, ADMA 2018, Nanjing, China, November 16–18, 2018, Proceedings (Lecture Notes in Computer Science #11323)

by Guojun Gan Bohan Li Xue Li Shuliang Wang

This book constitutes the refereed proceedings of the 14th International Conference on Advanced Data Mining and Applications, ADMA 2018, held in Nanjing, China in November 2018. The 23 full and 22 short papers presented in this volume were carefully reviewed and selected from 104 submissions. The papers were organized in topical sections named: Data Mining Foundations; Big Data; Text and Multimedia Mining; Miscellaneous Topics.

Advanced Data Mining and Applications: 13th International Conference, ADMA 2017, Singapore, November 5–6, 2017, Proceedings (Lecture Notes in Computer Science #10604)

by Gao Cong, Wen-Chih Peng, Wei Emma Zhang, Chengliang Li and Aixin Sun

This book constitutes the refereed proceedings of the 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, held in Singapore in November 2017. The 20 full and 38 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers were organized in topical sections named: database and distributed machine learning; recommender system; social network and social media; machine learning; classification and clustering methods; behavior modeling and user profiling; bioinformatics and medical data analysis; spatio-temporal data; natural language processing and text mining; data mining applications; applications; and demos.

Advanced Data Mining and Applications: 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12-15, 2016, Proceedings (Lecture Notes in Computer Science #10086)

by Jinyan Li, Xue Li, Shuliang Wang, Jianxin Li and Quan Z. Sheng

This book constitutes the proceedings of the 12th International Conference on Advanced Data Mining and Applications, ADMA 2016, held in Gold Coast, Australia, in December 2016. The 70 papers presented in this volume were carefully reviewed and selected from 105 submissions. The selected papers covered a wide variety of important topics in the area of data mining, including parallel and distributed data mining algorithms, mining on data streams, graph mining, spatial data mining, multimedia data mining, Web mining, the Internet of Things, health informatics, and biomedical data mining.

Advanced Data Analysis in Neuroscience: Integrating Statistical and Computational Models (Bernstein Series in Computational Neuroscience)

by Daniel Durstewitz

This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanatory frameworks, but become powerful, quantitative data-analytical tools in themselves that enable researchers to look beyond the data surface and unravel underlying mechanisms. Interactive examples of most methods are provided through a package of MatLab routines, encouraging a playful approach to the subject, and providing readers with a better feel for the practical aspects of the methods covered. "Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well as mathematically well versed Physicists. The book acts as a window to the issues, to the questions, and to the tools for finding the answers to interesting inquiries about brains and how they function." Henry D. I. Abarbanel Physics and Scripps Institution of Oceanography, University of California, San Diego “This book delivers a clear and thorough introduction to sophisticated analysis approaches useful in computational neuroscience. The models described and the examples provided will help readers develop critical intuitions into what the methods reveal about data. The overall approach of the book reflects the extensive experience Prof. Durstewitz has developed as a leading practitioner of computational neuroscience. “ Bruno B. Averbeck

An Advanced Course in Probability and Stochastic Processes

by Dirk P. Kroese Zdravko Botev

An Advanced Course in Probability and Stochastic Processes provides a modern and rigorous treatment of probability theory and stochastic processes at an upper undergraduate and graduate level. Starting with the foundations of measure theory, this book introduces the key concepts of probability theory in an accessible way, providing full proofs and extensive examples and illustrations. Fundamental stochastic processes such as Gaussian processes, Poisson random measures, Lévy processes, Markov processes, and Itô processes are presented and explored in considerable depth, showcasing their many interconnections. Special attention is paid to martingales and the Wiener process and their central role in the treatment of stochastic integrals and stochastic calculus. This book includes many exercises, designed to test and challenge the reader and expand their skillset. An Advanced Course in Probability and Stochastic Processes is meant for students and researchers who have a solid mathematical background and who have had prior exposure to elementary probability and stochastic processes. Key Features: Focus on mathematical understanding Rigorous and self-contained Accessible and comprehensive High-quality illustrations Includes essential simulation algorithms Extensive list of exercises and worked-out examples Elegant and consistent notation

An Advanced Course in Computational Nuclear Physics: Bridging the Scales from Quarks to Neutron Stars (Lecture Notes in Physics #936)

by Morten Hjorth-Jensen Maria Paola Lombardo Ubirajara Van Kolck

This graduate-level text collects and synthesizes a series of ten lectures on the nuclear quantum many-body problem. Starting from our current understanding of the underlying forces, it presents recent advances within the field of lattice quantum chromodynamics before going on to discuss effective field theories, central many-body methods like Monte Carlo methods, coupled cluster theories, the similarity renormalization group approach, Green’s function methods and large-scale diagonalization approaches. Algorithmic and computational advances show particular promise for breakthroughs in predictive power, including proper error estimates, a better understanding of the underlying effective degrees of freedom and of the respective forces at play. Enabled by recent improvements in theoretical, experimental and numerical techniques, the state-of-the art applications considered in this volume span the entire range, from our smallest components – quarks and gluons as the mediators of the strong force – to the computation of the equation of state for neutron star matter. The lectures presented provide an in-depth exposition of the underlying theoretical and algorithmic approaches as well details of the numerical implementation of the methods discussed. Several also include links to numerical software and benchmark calculations, which readers can use to develop their own programs for tackling challenging nuclear many-body problems.

Advanced Control of Industrial Processes: Structures and Algorithms (Advances in Industrial Control)

by Piotr Tatjewski

This book presents the concepts and algorithms of advanced industrial process control and on-line optimization within the framework of a multilayer structure. It describes the interaction of three separate layers of process control: direct control, set-point control, and economic optimization. The book features illustrations of the methodologies and algorithms by worked examples and by results of simulations based on industrial process models.

Advanced Construction Mathematics

by Surinder Virdi

Advanced Construction Mathematics covers the range of topics that a student must learn in order to achieve success in Level 3 and 4 mathematics for the Pearson BTEC National and BTEC HNC/HND in Construction, Building Services, and Civil Engineering. Packed with easy to follow examples, its 18 chapters cover algebra (equations, transposition and evaluation of formulae), differentiation, integration, statistics and numerous other core concepts and their application in the construction/civil engineering field. The book explains technical processes before applying mathematical techniques to solve practical problems which gradually build in complexity. Each chapter contains self-test exercises and answers and numerous illustrations to simplify the essential maths required at Levels 3 and 4. The book is also a useful recap or primer for students on BSc or non-cognate MSc Construction and Civil Engineering degrees.

Advanced Construction Mathematics

by Surinder Virdi

Advanced Construction Mathematics covers the range of topics that a student must learn in order to achieve success in Level 3 and 4 mathematics for the Pearson BTEC National and BTEC HNC/HND in Construction, Building Services, and Civil Engineering. Packed with easy to follow examples, its 18 chapters cover algebra (equations, transposition and evaluation of formulae), differentiation, integration, statistics and numerous other core concepts and their application in the construction/civil engineering field. The book explains technical processes before applying mathematical techniques to solve practical problems which gradually build in complexity. Each chapter contains self-test exercises and answers and numerous illustrations to simplify the essential maths required at Levels 3 and 4. The book is also a useful recap or primer for students on BSc or non-cognate MSc Construction and Civil Engineering degrees.

Advanced Concepts for Intelligent Vision Systems: 20th International Conference, ACIVS 2020, Auckland, New Zealand, February 10–14, 2020, Proceedings (Lecture Notes in Computer Science #12002)

by Jacques Blanc-Talon Patrice Delmas Wilfried Philips Dan Popescu Paul Scheunders

This book constitutes the proceedings of the 20th INternational Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2020, held in Auckland, New Zealand, in February 2020. The 48 papers presented in this volume were carefully reviewed and selected from a total of 78 submissions. They were organized in topical sections named: deep learning; biomedical image analysis; biometrics and identification; image analysis; image restauration, compression and watermarking; tracking, and mapping and scene analysis.

Advanced Computing Technologies and Applications: Proceedings of 2nd International Conference on Advanced Computing Technologies and Applications—ICACTA 2020 (Algorithms for Intelligent Systems)

by Hari Vasudevan Antonis Michalas Narendra Shekokar Meera Narvekar

This book features selected papers presented at the 2nd International Conference on Advanced Computing Technologies and Applications, held at SVKM’s Dwarkadas J. Sanghvi College of Engineering, Mumbai, India, from 28 to 29 February 2020. Covering recent advances in next-generation computing, the book focuses on recent developments in intelligent computing, such as linguistic computing, statistical computing, data computing and ambient applications.

Advanced Computing Strategies for Engineering: 25th EG-ICE International Workshop 2018, Lausanne, Switzerland, June 10-13, 2018, Proceedings, Part II (Lecture Notes in Computer Science #10864)

by Ian F. Smith Bernd Domer

This double volume set ( LNAI 10863-10864) constitutes the refereed proceedings of the 25th International Workshop, EG-ICE 2018, held in Lausanne, Switzerland, in June 2018. The 58 papers presented in this volume were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on Advanced Computing in Engineering, Computer Supported Construction Management, Life-Cycle Design Support, Monitoring and Control Algorithms in Engineering, and BIM and Engineering Ontologies.

Advanced Computing, Machine Learning, Robotics and Internet Technologies: First International Conference, AMRIT 2023, Silchar, India, March 10–11, 2023, Revised Selected Papers, Part II (Communications in Computer and Information Science #1954)

by Prodipto Das Shahin Ara Begum Rajkumar Buyya

This two-volume set constitutes selected papers presented during the First International Conference on Advanced Computing, Machine Learning, Robotics and Internet Technologies, AMRIT 2023, held in Silchar, India, in March 2023.The 20 full papers and 27 short papers presented were thoroughly reviewed and selected from 110 submissions. They cover the following topics: artificial intelligence, machine learning, natural language processing, image processing, data science, soft computing techniques, computer networks and security, computer architecture and algorithms.

Advanced Computing, Machine Learning, Robotics and Internet Technologies: First International Conference, AMRIT 2023, Silchar, India, March 10–11, 2023, Revised Selected Papers, Part I (Communications in Computer and Information Science #1953)

by Prodipto Das Shahin Ara Begum Rajkumar Buyya

This two-volume set constitutes selected papers presented during the First International Conference on Advanced Computing, Machine Learning, Robotics and Internet Technologies, AMRIT 2023, held in Silchar, India, in March 2023.The 20 full papers and 27 short papers presented were thoroughly reviewed and selected from 110 submissions. They cover the following topics: artificial intelligence, machine learning, natural language processing, image processing, data science, soft computing techniques, computer networks and security, computer architecture and algorithms.

Advanced Computing in Industrial Mathematics: 13th Annual Meeting of the Bulgarian Section of SIAM, December 18-20, 2018, Sofia, Bulgaria, Revised Selected Papers (Studies in Computational Intelligence #961)

by Ivan Georgiev Hristo Kostadinov Elena Lilkova

This book gathers the peer-reviewed proceedings of the 13th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'18, held in Sofia, Bulgaria. The general theme of BGSIAM'18 was industrial and applied mathematics with particular focus on: mathematical physics, numerical analysis, high performance computing, optimization and control, mathematical biology, stochastic modeling, machine learning, digitization and imaging, advanced computing in environmental, biomedical and engineering applications.

Advanced Computing in Industrial Mathematics: 15th Annual Meeting of the Bulgarian Section of SIAM, December 15-17, 2020, Sofia, Bulgaria, Revised Selected Papers (Studies in Computational Intelligence #1076)

by Ivan Georgiev Hristo Kostadinov Elena Lilkova

This book gathers the peer-reviewed proceedings of the 15th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'20, held in Sofia, Bulgaria. The general theme of BGSIAM'20 was industrial and applied mathematics with particular focus on mathematical physics, numerical analysis, high-performance computing, optimization and control, mathematical biology, stochastic modeling, machine learning, digitization and imaging, advanced computing in environmental, and biomedical and engineering applications.

Advanced Computing in Industrial Mathematics: 14th Annual Meeting of the Bulgarian Section of SIAM, December 17-19, 2019, Sofia, Bulgaria, Revised Selected Papers (Studies in Computational Intelligence #1111)

by Ivan Georgiev Hristo Kostadinov Elena Lilkova

This book gathers the peer-reviewed proceedings of the 14th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'19, held in Sofia, Bulgaria. The general theme of BGSIAM'19 was industrial and applied mathematics with particular focus on mathematical physics, numerical analysis, high-performance computing, optimization and control, mathematical biology, stochastic modeling, machine learning, digitization and imaging, and advanced computing in environmental, biomedical, and engineering applications.

Advanced Computing in Industrial Mathematics: Revised Selected Papers of the 10th Annual Meeting of the Bulgarian Section of SIAM December 21-22, 2015, Sofia, Bulgaria (Studies in Computational Intelligence #681)

by Krassimir Georgiev Michail Todorov Ivan Georgiev

This book presents recent research on Advanced Computing in Industrial Mathematics, which is one of the most prominent interdisciplinary areas and combines mathematics, computer science, scientific computations, engineering, physics, chemistry, medicine, etc. Further, the book presents the tools of Industrial Mathematics, which are based on mathematical models, and the corresponding computer codes, which are used to perform virtual experiments to obtain new data or to better understand the existing experimental results. The book gathers the peer-reviewed papers presented during the 10th Annual Meeting of the Bulgarian Section of SIAM (BGSIAM) from December 21 to 22, 2015 in Sofia, Bulgaria.

Advanced Computing in Industrial Mathematics: 11th Annual Meeting of the Bulgarian Section of SIAM December 20-22, 2016, Sofia, Bulgaria. Revised Selected Papers (Studies in Computational Intelligence #728)

by Krassimir Georgiev Michail Todorov Ivan Georgiev

This book presents recent research on Advanced Computing in Industrial Mathematics, which is one of the most prominent interdisciplinary areas, bringing together mathematics, computer science, scientific computations, engineering, physics, chemistry, medicine, etc. Further, the book presents the major tools used in Industrial Mathematics, which are based on mathematical models, and the corresponding computer codes, which are used to perform virtual experiments to obtain new data or to better understand previous experimental findings. The book gathers the peer-reviewed papers presented at the 11th Annual Meeting of the Bulgarian Section of SIAM (BGSIAM), from December 20 to 22, 2016 in Sofia, Bulgaria.

Advanced Computing in Industrial Mathematics: 12th Annual Meeting of the Bulgarian Section of SIAM December 20-22, 2017, Sofia, Bulgaria Revised Selected Papers (Studies in Computational Intelligence #793)

by Krassimir Georgiev Michail Todorov Ivan Georgiev

This book gathers the peer-reviewed proceedings of the 12th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM’17, held in Sofia, Bulgaria, in December 2017. The general theme of BGSIAM’17 was industrial and applied mathematics, with a particular focus on: high-performance computing, numerical methods and algorithms, analysis of partial differential equations and their applications, mathematical biology, control and uncertain systems, stochastic models, molecular dynamics, neural networks, genetic algorithms, metaheuristics for optimization problems, generalized nets, and Big Data.

Advanced Computing in Electron Microscopy

by Earl J. Kirkland

Image simulation has become a common tool in HREM (High Resolution Electron Microscopy) in recent years. However, the literature on the subject is scattered among many different journals and conference proceedings that have occurred in the last two or three decades. It is difficult for beginners to get started in this field. The principle method of image simulation has come to be known as simply the multislice method. This book attempts to bring the diverse information on image simulation together into one place and to provide a background on how to use the multislice method to simulate high resolution images in both conventional and scanning transmission electron microscopy. The main goals of image simulation include understanding the microscope and interpreting high resolution information in the recorded micrographs. This book contains sections on the theory of image formation and simulation as well as a more practical introduction on how to use the multislice method on real specimens. Also included with this book is a CD-ROM with working programs to perform image simulation. The source code as well as the executable code for IBM-PC and Apple Macintosh computers is included. Although the programs may not have a very elegant user interface by today's standards (simple command line dialog), the source code should be very portable to a variety of different computers. It has been compiled and run on Mac's, PC's and several different types of UNIX computers.

Advanced Computing and Intelligent Technologies: Proceedings of ICACIT 2021 (Lecture Notes in Networks and Systems #218)

by Vincenzo Piuri Monica Bianchini Rabindra Nath Shaw Sanjoy Das

This book gathers selected high-quality research papers presented at International Conference on Advanced Computing and Intelligent Technologies (ICACIT 2021) held at NCR New Delhi, India, during March 20–21, 2021, jointly organized by Galgotias University, India, and Department of Information Engineering and Mathematics Università Di Siena, Italy. It discusses emerging topics pertaining to advanced computing, intelligent technologies, and networks including AI and machine learning, data mining, big data analytics, high-performance computing network performance analysis, Internet of things networks, wireless sensor networks, and others. The book offers a valuable asset for researchers from both academia and industries involved in advanced studies.

Advanced Computing and Intelligent Technologies: Proceedings of ICACIT 2022 (Lecture Notes in Electrical Engineering #914)

by Rabindra Nath Shaw Sanjoy Das Vincenzo Piuri Monica Bianchini

This book gathers selected high-quality research papers presented at International Conference on Advanced Computing and Intelligent Technologies (ICACIT 2022), held at BIHER Chennai India, during March 12–13, 2022, jointly organized by Institute of Higher Education and Research Chennai 600073, Indira Gandhi National Tribal University, Regional Campus Manipur, India, and Department of Information Engineering and Mathematics Università Di Siena, Italy. It discusses emerging topics pertaining to advanced computing, intelligent technologies and networks including AI and machine learning, data mining, big data analytics, high performance computing network performance analysis, Internet of things networks, wireless sensor networks, and others. The book offers a valuable asset for researchers from both academia and industries involved in advanced studies.

Advanced Computing (Lecture Notes in Computational Science and Engineering #93)

by Michael Bader, Hans-Joachim Bungartz and Tobias Weinzierl

This proceedings volume collects review articles that summarize research conducted at the Munich Centre of Advanced Computing (MAC) from 2008 to 2012. The articles address the increasing gap between what should be possible in Computational Science and Engineering due to recent advances in algorithms, hardware, and networks, and what can actually be achieved in practice; they also examine novel computing architectures, where computation itself is a multifaceted process, with hardware awareness or ubiquitous parallelism due to many-core systems being just two of the challenges faced. Topics cover both the methodological aspects of advanced computing (algorithms, parallel computing, data exploration, software engineering) and cutting-edge applications from the fields of chemistry, the geosciences, civil and mechanical engineering, etc., reflecting the highly interdisciplinary nature of the Munich Centre of Advanced Computing.

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Showing 53,951 through 53,975 of 54,600 results