Advanced Methods In Statistics Data Science And Related Applications

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Advanced Methods In Statistics Data Science And Related Applications

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Author : Matilde Bini
language : en
Publisher: Springer Nature
Release Date : 2024-10-16

Advanced Methods In Statistics Data Science And Related Applications written by Matilde Bini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-16 with Computers categories.

This book contains a selection of the improved contributions submitted by participants at the conference of the Italian Statistical Society - SIS 2022 held in Caserta 22-24 June 2022. The scientific community of Italian statistics, which gathers around the SIS, is paying particular attention to the development of statistical techniques increasingly oriented toward the processing of large data, mainly, of complex data. The main goal is to provide the analysis of the data and the interpretability of the obtained results, with a view to decision support and the reliability of the data outcomes. The aim of this volume is to show some of the most relevant contributions of statistical and data analysis methods in preserving the quality of the information to be processed, especially when it comes from different, often non-official sources; as well as in the extraction of knowledge from complex data (textual, network, unstructured and multivalue) and in the explicability of results. Data Science today represents a broad domain of knowledge development from data, where statistical and data analysis methods can make an important contribution in the different domains where data management and processing are required. This volume is addressed to researchers but also to Ph.D. and MSc students in the field of Statistics and Data Science to acquaint them with some of the most recent developments towards which statistical research is orienting, in prevalence in Italy.

Comprehensive Remote Sensing

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Author : Shunlin Liang
language : en
Publisher: Elsevier
Release Date : 2017-11-08

Comprehensive Remote Sensing written by Shunlin Liang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-08 with Science categories.

Comprehensive Remote Sensing, Nine Volume Set covers all aspects of the topic, with each volume edited by well-known scientists and contributed to by frontier researchers. It is a comprehensive resource that will benefit both students and researchers who want to further their understanding in this discipline. The field of remote sensing has quadrupled in size in the past two decades, and increasingly draws in individuals working in a diverse set of disciplines ranging from geographers, oceanographers, and meteorologists, to physicists and computer scientists. Researchers from a variety of backgrounds are now accessing remote sensing data, creating an urgent need for a one-stop reference work that can comprehensively document the development of remote sensing, from the basic principles, modeling and practical algorithms, to various applications. Fully comprehensive coverage of this rapidly growing discipline, giving readers a detailed overview of all aspects of Remote Sensing principles and applications Contains ‘Layered content’, with each article beginning with the basics and then moving on to more complex concepts Ideal for advanced undergraduates and academic researchers Includes case studies that illustrate the practical application of remote sensing principles, further enhancing understanding

Computational Methods And Gis Applications In Social Science

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Author : Fahui Wang
language : en
Publisher: CRC Press
Release Date : 2023-08-16

Computational Methods And Gis Applications In Social Science written by Fahui Wang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-16 with Technology & Engineering categories.

This textbook integrates GIS, spatial analysis, and computational methods for solving real-world problems in various policy-relevant social science applications. Thoroughly updated, the third edition showcases the best practices of computational spatial social science and includes numerous case studies with step-by-step instructions in ArcGIS Pro and open-source platform KNIME. Readers sharpen their GIS skills by applying GIS techniques in detecting crime hotspots, measuring accessibility of primary care physicians, forecasting the impact of hospital closures on local community, or siting the best locations for business. FEATURES Fully updated using the latest version of ArcGIS Pro and open-source platform KNIME Features two brand-new chapters on agent-based modeling and big data analytics Provides newly automated tools for regionalization, functional region delineation, accessibility measures, planning for maximum equality in accessibility, and agent-based crime simulation Includes many compelling examples and real-world case studies related to social science, urban planning, and public policy Provides a website for downloading data and programs for implementing all case studies included in the book and the KNIME lab manual Intended for students taking upper-level undergraduate and graduate-level courses in quantitative geography, spatial analysis, and GIS applications, as well as researchers and professionals in fields such as geography, city and regional planning, crime analysis, public health, and public administration.

Data Science In Context

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Author : Alfred Z. Spector
language : en
Publisher: Cambridge University Press
Release Date : 2022-10-20

Data Science In Context written by Alfred Z. Spector and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-20 with Computers categories.

Data science is the foundation of our modern world. It underlies applications used by billions of people every day, providing new tools, forms of entertainment, economic growth, and potential solutions to difficult, complex problems. These opportunities come with significant societal consequences, raising fundamental questions about issues such as data quality, fairness, privacy, and causation. In this book, four leading experts convey the excitement and promise of data science and examine the major challenges in gaining its benefits and mitigating its harms. They offer frameworks for critically evaluating the ingredients and the ethical considerations needed to apply data science productively, illustrated by extensive application examples. The authors' far-ranging exploration of these complex issues will stimulate data science practitioners and students, as well as humanists, social scientists, scientists, and policy makers, to study and debate how data science can be used more effectively and more ethically to better our world.

Data Science

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Author : Ivo D. Dinov
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2021-12-06

Data Science written by Ivo D. Dinov and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-06 with Computers categories.

The amount of new information is constantly increasing, faster than our ability to fully interpret and utilize it to improve human experiences. Addressing this asymmetry requires novel and revolutionary scientific methods and effective human and artificial intelligence interfaces. By lifting the concept of time from a positive real number to a 2D complex time (kime), this book uncovers a connection between artificial intelligence (AI), data science, and quantum mechanics. It proposes a new mathematical foundation for data science based on raising the 4D spacetime to a higher dimension where longitudinal data (e.g., time-series) are represented as manifolds (e.g., kime-surfaces). This new framework enables the development of innovative data science analytical methods for model-based and model-free scientific inference, derived computed phenotyping, and statistical forecasting. The book provides a transdisciplinary bridge and a pragmatic mechanism to translate quantum mechanical principles, such as particles and wavefunctions, into data science concepts, such as datum and inference-functions. It includes many open mathematical problems that still need to be solved, technological challenges that need to be tackled, and computational statistics algorithms that have to be fully developed and validated. Spacekime analytics provide mechanisms to effectively handle, process, and interpret large, heterogeneous, and continuously-tracked digital information from multiple sources. The authors propose computational methods, probability model-based techniques, and analytical strategies to estimate, approximate, or simulate the complex time phases (kime directions). This allows transforming time-varying data, such as time-series observations, into higher-dimensional manifolds representing complex-valued and kime-indexed surfaces (kime-surfaces). The book includes many illustrations of model-based and model-free spacekime analytic techniques applied to economic forecasting, identification of functional brain activation, and high-dimensional cohort phenotyping. Specific case-study examples include unsupervised clustering using the Michigan Consumer Sentiment Index (MCSI), model-based inference using functional magnetic resonance imaging (fMRI) data, and model-free inference using the UK Biobank data archive. The material includes mathematical, inferential, computational, and philosophical topics such as Heisenberg uncertainty principle and alternative approaches to large sample theory, where a few spacetime observations can be amplified by a series of derived, estimated, or simulated kime-phases. The authors extend Newton-Leibniz calculus of integration and differentiation to the spacekime manifold and discuss possible solutions to some of the "problems of time". The coverage also includes 5D spacekime formulations of classical 4D spacetime mathematical equations describing natural laws of physics, as well as, statistical articulation of spacekime analytics in a Bayesian inference framework. The steady increase of the volume and complexity of observed and recorded digital information drives the urgent need to develop novel data analytical strategies. Spacekime analytics represents one new data-analytic approach, which provides a mechanism to understand compound phenomena that are observed as multiplex longitudinal processes and computationally tracked by proxy measures. This book may be of interest to academic scholars, graduate students, postdoctoral fellows, artificial intelligence and machine learning engineers, biostatisticians, econometricians, and data analysts. Some of the material may also resonate with philosophers, futurists, astrophysicists, space industry technicians, biomedical researchers, health practitioners, and the general public.

Data Science For Covid 19

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Author : Utku Kose
language : en
Publisher: Academic Press
Release Date : 2021-10-22

Data Science For Covid 19 written by Utku Kose and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Science categories.

Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques for the detection, mitigation, treatment and elimination of the COVID-19 virus. At this point, Cognitive Data Science is the most powerful tool for researchers to fight COVID-19. Thanks to instant data-analysis and predictive techniques, including Artificial Intelligence, Machine Learning, Deep Learning, Data Mining, and computational modeling for processing large amounts of data, recognizing patterns, modeling new techniques, and improving both research and treatment outcomes is now possible. - Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and the treatment of the COVID-19 virus - Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including the wide variety of impacts the virus is having on societies and medical practice - Presents insights into innovative, data-oriented modeling and predictive techniques from COVID-19 researchers around the world, including geoprocessing and tracking, lab data analysis, and theoretical views on a variety of technical applications - Includes real-world feedback and user experiences from physicians and medical staff from around the world for medical treatment perspectives, public safety policies and impacts, sociological and psychological perspectives, the effects of COVID-19 in agriculture, economies, and education, and insights on future pandemics

Data Science And Analytics With Python R And Spss Programming

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Author : V.K. Jain
language : en
Publisher: KHANNA PUBLISHING HOUSE
Release Date :

Data Science And Analytics With Python R And Spss Programming written by V.K. Jain and has been published by KHANNA PUBLISHING HOUSE this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

The Book has been written completely as per AICTE recommended syllabus on "Data Sciences". SALIENT FEATURES OF THE BOOK: Explains how data is collected, managed and stored for data science. With complete courseware for understand the key concepts in data science including their real-world applications and the toolkit used by data scientists. Implement data collection and management. Provided with state of the arts subjectwise. With all required tutorials on R, Python and Bokeh, Anaconda, IBM SPSS-21 and Matplotlib.

Data Analysis Machine Learning And Applications

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Author : Christine Preisach
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-04-13

Data Analysis Machine Learning And Applications written by Christine Preisach and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-13 with Computers categories.

Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.

Language And Text

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Author : Adam Pawłowski
language : en
Publisher: John Benjamins Publishing Company
Release Date : 2021-12-15

Language And Text written by Adam Pawłowski and has been published by John Benjamins Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-15 with Language Arts & Disciplines categories.

Specialists in quantitative linguistics the world over have recourse to a solid and universal methodology. These days, their methods and mathematical models must also respond to new communication phenomena and the flood of data produced daily. While various disciplines (computer science, media science) have different ways of processing this onslaught of information, the linguistic approach is arguably the most relevant and effective. This book includes recent results from many renowned contemporary practitioners in the field. Our target audiences are academics, researchers, graduate students, and others involved in linguistics, digital humanities, and applied mathematics.

The Ai Lead

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Author : Brian Lambert, PhD
language : en
Publisher: Digital Command
Release Date : 2025-01-14

The Ai Lead written by Brian Lambert, PhD and has been published by Digital Command this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-14 with Business & Economics categories.

In today’ss AI-driven world, businesses that fail to harness the power of data will be left behind. AI Lead: Overcoming Data Drag to Accelerate Digital Dominance is a game-changing guide for leaders, executives, and digital strategists who need to master the intersection of AI, data, and business impact. Written by industry expert Brian Lambert, PhD, this book provides a blueprint for overcoming “data drag” - the inefficiencies caused by poor data practices - that slow down decision-making, innovation, and organizational agility. Through real-world examples, actionable frameworks, and a strategic roadmap, AI Lead empowers readers to: + Identify and eliminate data bottlenecks that hinder AI adoption + Develop an AI-first leadership mindset to drive digital transformation + Enhance operational efficiency through better data governance + Bridge the gap between IT and business strategy for seamless AI execution + Foster a culture of digital fluency to future-proof careers and organizations Whether you’re an executive looking to optimize AI strategies, an IT leader aiming to improve data infrastructure, or a transformation champion navigating digital disruption, AI Lead equips you with the tools to turn data into a competitive advantage. Master Change. Lead with Command. Dominate the AI Age. Keywords: AI Leadership, Data Drag, Digital Transformation, Organizational Agility, Data Strategy, AI-Driven Decision Making, Business Innovation, Customer Experience, Operational Efficiency, Technology Integration