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Книги з теми "ANALYZE BIG DATA"

Автор: Grafiati

Опубліковано: 11 вересня 2023

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1

Cutt, Shannon, ed. Practical Statistics for Data Scientists: 50 Essential Concepts. Beijing: O’Reilly Media, 2017.

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2

D, Baxevanis Andreas, and Ouellette B. F. Francis, eds. Bioinformatics: A practical guide to the analysis of genes and proteins. 2nd ed. New York, NY: Wiley-Interscience, 2001.

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3

Python for Finance: Analyze Big Financial Data. O'Reilly Media, Incorporated, 2014.

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4

Python for Finance: Analyze Big Financial Data. O'Reilly Media, 2014.

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5

Python for Finance: Analyze Big Financial Data. O'Reilly Media, Incorporated, 2014.

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6

Vanaria, Von. Big Data Solutions : Guides for Beginners to Analyze Big Data Using Python and C++ Programming: C++ Programming Language. Independently Published, 2021.

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7

Pasupuleti, Pradeep, and Beulah Salome Purra. Data Lake Development with Big Data: Explore Architectural Approaches to Building Data Lakes That Ingest, Index, Manage, and Analyze Massive Amounts of Data Using Big Data Technologies. Packt Publishing, Limited, 2015.

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8

Shilpi and Sumit Gupta. Real-Time Big Data Analytics: Design, Process, and Analyze Large Sets of Complex Data in Real Time. Packt Publishing, Limited, 2016.

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9

Lai, Rudy, and Bartłomiej Potaczek. Hands-On Big Data Analytics with Pyspark: Analyze Large Datasets and Discover Techniques for Testing, Immunizing, and Parallelizing Spark Jobs. Packt Publishing, Limited, 2019.

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10

Kearn, Marvin. Great Apartment Buildings : Learn the Tricks and Tips on How to Analyze Big Apartment Buildings: How to Find the Data for Big Apartment Buildings. Independently Published, 2021.

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11

Big Data. Rewolucja: Efektywna analiza danych. Warszawa, Polska: MTBiznes, 2017.

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12

Computational Social Science: Die Analyse Von Big Data. Nomos Verlagsgesellschaft, 2018.

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13

Macnish, Kevin, and Jai Galliott, eds. Big Data and Democracy. Edinburgh University Press, 2020. http://dx.doi.org/10.3366/edinburgh/9781474463522.001.0001.

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Анотація:

This edited collection tackles subjects that have arisen as a result of new capabilities to collect, analyse and use vast quantities of data using complex algorithms. Questions tackled include what is wrong with targeted advertising in political campaigns, whether echo chambers really are a matter of genuine concern, what is the impact of data collection through social media and other platforms on questions of trust in society and is there a problem of opacity as decision-making becomes increasingly automated? The contributors consider potential solutions to these challenges and discuss whether an ethical compass is available or even feasible in an ever more digitized and monitored world. The editors bring together original research on the philosophy of big data and democracy from leading international authors, with recent examples and case references – including the 2016 Brexit Referendum, the Leveson Inquiry and the Edward Snowden leaks – and combine them in one authoritative volume at time of great political turmoil.

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14

Rust, Holger. Virtuelle Bilderwolken: Eine qualitative Big Data-Analyse der Geschmackskulturen im Internet. Springer VS, 2016.

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15

Rust, Holger. Virtuelle Bilderwolken: Eine Qualitative Big Data-Analyse der Geschmackskulturen Im Internet. Springer Vieweg. in Springer Fachmedien Wiesbaden GmbH, 2016.

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16

Schwingungen von Windenergieanlagen 2019. VDI Verlag, 2019. http://dx.doi.org/10.51202/9783181023464.

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Анотація:

Dieser VDI-Bericht ist ausschließlich als PDF-Datei erschienen! Sie möchten gerne erfahren, welche Themen auf der 10. VDI-Fachtagung in Bremen präsentiert wurden? Inhalt Eröffnung Erkenntnisse aus digitalisierten Daten von über 3000 Windenergieanlagen im Betrieb 1 B. Hahn, S. Faulstich, Fraunhofer IEE, Kassel BIG DATA Auswertungen und Analysen von Betriebsdaten I Big Data – Smart Data, analytische Datenauswertung von Betriebsdaten 17 W. Holweger, Schaeffler Technologies AG & Co. KG, Herzogenaurach; F. Harzendorf, B. Azzam, CWD RWTH Aachen University, Aachen; J. Fliege, Universität Southampton, Southampton, UK Felderfahrung von Anlagen und Windparks I MSA (Messsystemanalyse) eines back-to-back Getriebeprüfstands 29 T. Jacob (M.Sc.) (VDI), Flender GmbH, Voerde; M. Blomeyer, Flender GmbH, Bocholt Felderfahrung und Ergebnisse aus großen Windparks: Von der Zuverlässigkeits- und CMS-Analyse zur Prognosefähigkeit 41 S. Mtauweg, V. Meimann, MML Solutions GmbH; H. Fritsch, U.

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17

Murtagh, Fionn. Data Science Foundations: Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics. Taylor & Francis Group, 2017.

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18

Murtagh, Fionn. Data Science Foundations: Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics. Taylor & Francis Group, 2017.

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19

Murtagh, Fionn. Data Science Foundations: Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics. Taylor & Francis Group, 2017.

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20

Schröder, Michael, and Axel Schwanebeck, eds. Big Data - In den Fängen der Datenkraken. Nomos Verlagsgesellschaft mbH & Co. KG, 2019. http://dx.doi.org/10.5771/9783748904373.

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Анотація:

Our beautiful, new digital world has a come at a price, which we are paying by relinquishing our personal data–while we are shopping, driving our cars, and chatting and surfing on the Internet. However, the intelligent algorithms needed to process this data pose a threat to freedom in our society. They analyse and evaluate us, while predicting our behaviour. Big data and data mining are the business models of the future. What does all this mean for politics, the economy, journalism and political communication? Do we have to defend basic human rights and human dignity against the digital revolution? Do we need new laws and a code of ethics for algorithms? And how will politics, the media and democracy function under these new conditions? In this book, experts from a variety of academic fields, journalism and politics discuss these questions in terms of the future and society. With contributions by Johanna Haberer, Yvonne Hofstetter, Sabine Leutheusser-Schnarrenberger, Klaus Mainzer, Daniel Moßbrucker, Peter Schaar, Michael Schröder, Axel Schwanebeck and Thomas Zeilinger.

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21

Sutmöller, Nadine, and Nadine Sutmoller. Big Data Im Spannungsfeld Von Wirtschaft und Gerechtigkeit: Eine Analyse Nach John Rawls. Nomos Verlagsgesellschaft, 2021.

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22

Schwingungen von Windenergieanlagen 2017. VDI Verlag, 2017. http://dx.doi.org/10.51202/9783181023013.

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Geräusche, Schallmessungen und Schallübertragung Strukturüberwachung von Offshore Windenergieanlagen Anregungsmechanismen und Optimierungsmaßnahmen Condition Monitoring und Schadensanalyse BIG DATA und Flottenmanagement Maßnahmen zur Schwingungsminderung Simulation und Analyse des dynamischen Verhaltens ...

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23

Big Data Analytics and Intelligent Techniques for Smart Cities. Taylor & Francis Group, 2021.

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24

Jue, Melody, and Rafico Ruiz, eds. Saturation. Duke University Press, 2021. http://dx.doi.org/10.1215/9781478013044.

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Анотація:

Bringing together media studies and environmental humanities, the contributors to Saturation develop saturation as a heuristic to analyze phenomena in which the elements involved are difficult or impossible to separate. In ordinary language, saturation describes the condition of being thoroughly soaked, while in chemistry it is the threshold at which something can be maximally dissolved or absorbed in a solution. Contributors to this collection expand notions of saturation beyond water to consider saturation in sound, infrastructure, media, Big Data, capitalism, and visual culture. Essays include analyses of the thresholds of HIV detectability in bloodwork, militarism's saturation of oceans, and the deleterious effects of the saturation of cellphone and wi-fi signals into the human body. By channeling saturation to explore the relationship between media, the environment, technology, capital, and the legacies of settler colonialism, Saturation illuminates how elements, the natural world, and anthropogenic infrastructures, politics, and processes exist in and through each other. Contributors. Marija Cetinić, Jeff Diamanti, Bishnupriya Ghosh, Lisa Yin Han, Stefan Helmreich, Mél Hogan, Melody Jue, Rahul Mukherjee, Max Ritts, Rafico Ruiz, Bhaskar Sarkar, John Shiga, Avery Slater, Janet Walker, Joanna Zylinska

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25

Alger, Bradley E. Defense of the Scientific Hypothesis. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190881481.001.0001.

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This book explains and defends the scientific hypothesis. Explanation is needed to counteract the misinformation and misunderstanding about the hypothesis that even scientists have concerning its nature and place in the tapestry of modern science. A survey revealed that most biological scientists receive little or no formal training in scientific thinking. Defense is needed because the hypothesis is under attack by critics who claim it is irrelevant to science. Defense is important, too, because the hypothesis is perhaps the major element in scientific thinking, and familiarity with it is necessary for an understanding of modern science and scientific thinking. The public needs to understand the hypothesis in order to appreciate and evaluate scientific controversies (e.g., global climate change, vaccine safety, etc.). The first chapters thoroughly describe and analyze in elementary terms the scientific hypothesis and examine various kinds of science. Following chapters that review the hypothesis in the context of the Reproducibility Crisis and present survey data, two chapters assess cognitive matters that affect the hypothesis. In a series of chapters, the book makes practical and policy recommendations for teaching and learning about the hypothesis. The final chapter considers two possible futures for the hypothesis in science as the Big Data revolution looms: in one scenario, the hypothesis is displaced by the Big Data Mindset that forgoes understanding in favor of correlation and prediction. In the other, robotic science incorporates the hypothesis into mechanized laboratories guided by artificial intelligence. An epilogue envisions a third way—the Centaur Scientist, a symbiotic relationship of human scientists and computers.

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26

Pavlović, Vladan. KONSTRUKCIONA GRAMATIKA I KOLOSTRUKCIONA ANALIZA https://doi. Filozofski fakultet Niš, 2021. http://dx.doi.org/10.46630/kga.2021.

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Анотація:

Ova monografija proistekla je iz mog interesovanja za konstrukcione pristupe uopšte i goldbergovsku konstrukcionu gramatiku posebno. To interesovanje podstakla je prof. dr Katarina Rasulić, koja je bila mentor mog magistarskog rada, odbranjenog 2007. godine na Filološkom fakultetu Univerziteta u Beogradu, čiji je deo teorijskih osnova činila upravo goldbergovska konstrukciona gramatika. Datu porodicu teorija u okviru kognitivne lingvistike u užem smislu, a posebno pomenutu goldbergovsku konstrukcionu gramatiku, do danas smatram najsmislenijim pristupom u oblasti proučavanja gramatičko-leksičkog interfejsa. Uz to, ova monografija proizašla je i iz mog interesovanja za kolostrukcionu analizu, na koju mi je pažnju takođe skrenula prof. Rasulić upravo u vreme pisanja magistarskog rada, kada je dati statistički postupak bio tek u povoju, a kada sam i sâm bio vrlo skeptičan po pitanju korišćenja strogih statističkih procedura u lingvističkoj analizi.

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27

Halperin, Sandra, and Oliver Heath. 7. What is Data? Oxford University Press, 2017. http://dx.doi.org/10.1093/hepl/9780198702740.003.0007.

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This chapter considers the main types of data used in Politics and International Relations (IR), as well as the main criteria by which to judge whether the data collected is good or not. It first describes the steps involved in the process of thinking about what data or evidence is relevant to answering a research question before discussing the importance of addressing issues of validity and reliability in research. Some of these issues are illustrated by referring to recent attempts to measure corruption, a major topic of interest in Politics and IR. The chapter also examines the issue of case selection as well as the collection of qualitative and quantitative data using methods such as interviewing and observation. Finally, it analyses the so-called ‘big data’ revolution in data collection and analysis and provides a data quality checklist.

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28

Data Science for Mathematicians. Taylor & Francis Group, 2020.

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29

Carter, Nathan. Data Science for Mathematicians. Taylor & Francis Group, 2020.

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30

Carter, Nathan. Data Science for Mathematicians. Taylor & Francis Group, 2020.

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31

Carter, Nathan. Data Science for Mathematicians. Taylor & Francis Group, 2020.

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32

Carter, Nathan. Data Science for Mathematicians. Taylor & Francis Group, 2020.

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33

Lünich, Marco. Glaube an Big Data: Eine Analyse Gesellschaftlicher Überzeugungen Von Erkenntnis- und Nutzengewinnen Aus Digitalen Daten. Springer Fachmedien Wiesbaden GmbH, 2022.

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34

Big Data Work Dispelling The Myths Uncovering The Opportunities. Harvard Business Press, 2014.

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35

Grönke, Kai, Markus Kirchmann, Ronald Gleich, and Jörg Leyk. Strategische Unternehmensführung mit Advanced Analytics: Neue Möglichkeiten von Big Data für Planung und Analyse erkennen und nutzen. Haufe Lexware GmbH, 2017.

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36

Jockers, Matthew L. Theme. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252037528.003.0008.

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Анотація:

This chapter demonstrates how big data and computation can be used to identify and track recurrent themes as the products of external influence. It first considers the limitations of the Google Ngram Viewer as a tool for tracing thematic trends over time before turning to Douglas Biber's Corpus Linguistics: Investigating Language Structure and Use, a primer on various factors complicating word-focused text analysis and the subsequent conclusions one might draw regarding word meanings. It then discusses the results of the author's application of latent Dirichlet allocation (LDA) to a corpus of 3,346 nineteenth-century novels using the open-source MALLET (MAchine Learning for LanguagE Toolkit), a software package for topic modeling. It also explains the different types of analyses performed by the author, including text segmentation, word chunking, and author nationality, gender and time-themes relationship analyses. The thematic data from the LDA model reveal the degree to which author nationality, author gender, and date of publication could be predicted by the thematic signals expressed in the nineteenth-century novels corpus.

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37

It's All Analytics!: The Foundations of AI, Big Data, and Data Science Landscape for Professionals in Healthcare, Business, and Government. Productivity Press, 2020.

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38

Miner, Gary D., and Scott Burk. It's All Analytics!: The Foundations of Al, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government. Productivity Press, 2022.

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39

Miner, Gary, and Scott Burk. It's All Analytics!: The Foundations of AI, Big Data, and Data Science Landscape for Professionals in Healthcare, Business, and Government. Productivity Press, 2020.

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40

Small, Mario Luis. Someone To Talk To. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190661427.001.0001.

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Анотація:

When people are facing difficulties, they often feel the need for a confidant—a person to vent to or talk things through with who will offer sympathy or understanding. How do they decide on whom to rely? In theory, the answer seems obvious: if the matter is personal, they will turn to a spouse, a family member, or someone otherwise close. In practice, what people actually do often belies these expectations. This book follows a group of graduate students as they cope with the stress of their first year in their programs, probing how they choose confidants over the course of their everyday experiences and unraveling the implications of the process. The book then tests its explanations against data on national populations. It shows that rather than consistently rely on their “strong ties,” people often take pains to avoid close friends and family, because these are too fraught with complex expectations. People often confide in “weak ties,” as their fear that their trust could be misplaced is overcome by their need for one who understands. In fact, people may find themselves confiding in acquaintances and even strangers unexpectedly, without much reflection on the consequences. Amid a growing wave of big data and large-scale network analysis, the book returns to the basic questions of who we connect with, how, and why, and upends decades of conventional wisdom on how we should think about and analyze social networks.

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41

Kern, Margaret L., and Howard S. Friedman. Health Psychology. Edited by Thomas A. Widiger. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199352487.013.2.

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As research on personality and health has moved to developing multitrait, multioutcome models, the five factor approach has shown excellent utility for understanding health, including physical and mental health, longevity, cognitive function, social competence, and productivity. Drawing on a growing arsenal of advanced statistical techniques, studies are testing complex models to explain how personality influences health. Health behaviors, social situations, physiological changes, and various indirect and moderating factors are important pathways connecting personality and health, and reciprocally influence one another. Future personality research will benefit from interdisciplinary approaches, including integrative data analyses of archival data, big data analyses, neuroscientific approaches, and lifespan epidemiology. Bringing together different types of data, innovative methods, and well-specified theories offers the potential to understand the personality–health model in ways never before imagined. Identifying pathways and key factors in turn will inform effective intervention to help more people live healthier, more productive lives.

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42

Farias, Pedro Lima Gondim de, and Marcus Aurélio de Freitas Barros. Advocacia na Era Digital: Uma análise sobre possíveis impactos práticos e jurídicos das novas tecnologias na dinâmica da advocacia privada. Brazil Publishing, 2021. http://dx.doi.org/10.31012/978-65-5861-213-1.

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This work aims to analyze the possible practical and legal repercussions of the implementation of technologies characteristic of the digital age in the dynamics of advocacy. Considering the increasing influence that scientific advances have exercised not only in human life, but especially in the ways of working and in the models of the professions, the objective was to prospectively investigate the transformations of this context in advocacy. In order to improve the understanding of the research, three common sectors-activities were separated between the more traditional advocacy: manual labor; systems and departments, highlighting the most recurring bottlenecks. Ahead, there were also three technologies highlighted in the technological revolution, which were: artificial intelligence; automation of legal documents and big data. In the meantime, possible resistance factors between law and technology were also discussed. Finally, through a bibliographic and exploratory methodological process, the research explored possible consequences of the direct insertion of these new technologies in each specific sector of traditional law, considering the functionalities and the problems that would be solved. Thus, there were several repercussions, both practical and legal, including the financial, methodological, strategic and organizational logistics of the offices, among which were mentioned: gain of time; fees. internal costs; data-based procedural strategy, and more. Still, in addition to the realization of the high probability of changes in the lawyer's practice, there was a need to seek solutions that really connect the law to innovations in this new scenario, with emphasis on the contracting of services offered by lawtechs.

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43

Fleury, James, Bryan Hikari Hartzheim, and Stephen Mamber, eds. The Franchise Era. Edinburgh University Press, 2019. http://dx.doi.org/10.3366/edinburgh/9781474419222.001.0001.

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Анотація:

As Hollywood shifts towards the digital era, the role of the media franchise has become more prominent. Over a series of essays by a range of international scholars, this edited collection argues that the franchise is now an integral element of American media culture. As such, the collection explores the production, distribution, and marketing of franchises as a historical form of media-making. In particular, the essays analyze the complex industrial practice of managing franchises across interconnected online platforms with a global scope, presenting a network of scholarly texts that critically look at the collision of new and old industrial logics against an ever more fragmented and consolidated mediascape. The authors address how traditional incumbents like film studios and television networks have responded to the rise of big data, Silicon Valley companies like Facebook, Apple, Amazon, Netflix, and Google; the ways in which legacy franchises are adapting to new media platforms and technologies; the significant historical continuities and deviations in franchise-making and how they shape the representation of on-screen texts across digital displays; and, finally, how emerging media formats are expanding the possibility for transmedia experiences. In this regard, The Franchise Era: Managing Media in the Digital Economy offers an in-depth analysis of the tectonic shifts that have disrupted entertainment companies in the twenty-first century, demonstrating that the media franchise stands front and center in this high-stakes environment.

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44

Millard, Christopher, ed. Cloud Computing Law. 2nd ed. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198716662.001.0001.

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Анотація:

This book examines in detail the legal implications of cloud computing. In essence, 'the cloud' is a way of delivering computing resources as a utility service via the Internet. It is evolving very rapidly with substantial investments being made in infrastructure, platforms, and applications, all delivered 'as a service'. The demand for cloud resources is enormous, driven by such developments as the deployment on a vast scale of mobile apps and the rapid emergence of 'Big Data'. The book explains what cloud computing is and how it works; analyses contractual relationships between cloud service providers and their customers, as well as the complex roles of intermediaries; and explores specific arrangements for public sector cloud procurement and questions about ownership of data in clouds. It also studies the protection of personal data in clouds, governance challenges relating to access to data in clouds by law enforcement authorities, ways of facilitating competition between cloud service providers, and the consumer protection implications of cloud computing.

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45

Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python. O'Reilly Media, Incorporated, 2020.

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46

Trobia, Alberto, and Fabio M. Lo Verde. Italian Amateur Pop-Rock Musicians on Facebook. Edited by Roger Mantie and Gareth Dylan Smith. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190244705.013.8.

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This chapter investigates how and why amateur musicians use social networking sites, employing a mixed-methods approach. Attention is focused on four big Italian Facebook communities of pop-rock musicians: drums, bass, guitar, and keyboard players (overall, 2,101 active users), analyzing the relational and textual data extracted from the web. The chapter analyzes the network structures emerging from the interactions among the users. It also identifies and maps the main areas of discussion (sound shaping, studio recording, marketplace, musical references, computer production, and relations) and the latent semantic dimension characterizing Facebook users’ activities, through social network analysis and lexical correspondence analysis. Meanings, values, aesthetics, and representations of amateur music making, emerging from the data, are framed within two orthogonal dimensions: theory versus praxis, and competence versus music production. The Italian singularity is then explained with respect to this space. Some theoretical conclusions are finally drawn.

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47

Chen, Yi-Ping Phoebe. Bioinformatics Technologies. Springer, 2014.

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48

Chen, Yi-Ping Phoebe. Bioinformatics Technologies. Springer, 2005.

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49

Arduino, Mik. Python for Data Science: Deep Machine Learning Algorithms in Python and Artificial Intelligence. Crash Course to Measure Value of Big Data and Analyzes What Matters to Live by Computer Programming. Independently Published, 2019.

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Martin, Philip. Migration Costs of Returning Workers. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198808022.003.0005.

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Анотація:

This chapter analyzes data on what workers—interviewed as they returned from jobs in Gulf Cooperation Council countries—paid several years earlier at home to get their jobs. The most important finding is the big difference in cost by corridor. The gap between the highest and lowest cost corridor was 9 to 1, reflecting the average $4,400 paid by Pakistanis returning from Saudia Arabia versus the $500 paid by Filipinos returning from Qatar. Earnings gaps were much smaller, ranging from a low of $350 a month for Ethiopians returning from Saudi Arabia to $600 for Indians returning from Qatar. The fact that costs vary much more than earnings suggests that differing conditions in migrant-sending countries might explain why some workers pay much more than others.

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