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Author: Gerald Sim
Publisher: Taylor & Francis
ISBN: 1040102654
Category : Social Science
Languages : en
Pages : 147
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Book Description
This book examines the influence of key films on public understanding of big data and the algorithmic systems that structure our digitally mediated lives. From star-powered blockbusters to civic-minded documentaries positioned to facilitate weighty debates about artificial intelligence, these texts frame our discourse and mediate our relationship to technology. Above all, they impact society’s abilities to regulate AI and navigate big tech’s political and economic maneuvers to achieve market dominance and regulatory capture. Foregrounding data politics with close readings of key films like Moneyball, Minority Report, The Social Dilemma, and Coded Bias, Gerald Sim reveals compelling ways in which films and tech industry–adjacent media define apprehension of AI. With the mid-2010s techlash in danger of fizzling out, Screening Big Data explores the relationship between this resistance and cultural infrastructure while highlighting the urgent need to refocus attention onto how technocentric media occupy the public imagination. This book will interest students and scholars of film and media studies, digital culture, critical data studies, and technopolitics.
Author: Gerald Sim
Publisher: Taylor & Francis
ISBN: 1040102654
Category : Social Science
Languages : en
Pages : 147
Get Book Here
Book Description
This book examines the influence of key films on public understanding of big data and the algorithmic systems that structure our digitally mediated lives. From star-powered blockbusters to civic-minded documentaries positioned to facilitate weighty debates about artificial intelligence, these texts frame our discourse and mediate our relationship to technology. Above all, they impact society’s abilities to regulate AI and navigate big tech’s political and economic maneuvers to achieve market dominance and regulatory capture. Foregrounding data politics with close readings of key films like Moneyball, Minority Report, The Social Dilemma, and Coded Bias, Gerald Sim reveals compelling ways in which films and tech industry–adjacent media define apprehension of AI. With the mid-2010s techlash in danger of fizzling out, Screening Big Data explores the relationship between this resistance and cultural infrastructure while highlighting the urgent need to refocus attention onto how technocentric media occupy the public imagination. This book will interest students and scholars of film and media studies, digital culture, critical data studies, and technopolitics.
Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 0128181478
Category : Science
Languages : en
Pages : 312
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Book Description
Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data. Examines the methodology and requirements for development of big data architecture, big data modeling, big data as a service, big data analytics, and more Discusses big data applications for intelligent healthcare management, such as revenue management and pricing, predictive analytics/forecasting, big data integration for medical data, algorithms and techniques, etc. Covers the development of big data tools, such as data, web and text mining, data mining, optimization, machine learning, cloud in big data with Hadoop, big data in IoT, and more
Author: Nataraj Dasgupta
Publisher: Packt Publishing Ltd
ISBN: 1783554401
Category : Computers
Languages : en
Pages : 402
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Book Description
Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.
Author: Vincent Morelli
Publisher: Elsevier
ISBN: 9780323661300
Category : Medical
Languages : en
Pages : 274
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Book Description
In this comprehensive look at adolescent screening and holistic health in the technology age, Dr. Vincent Morelli reviews the history of the adolescent health screen, what is being used now, and what needs to be considered in the future. An ideal resource for primary care physicians, pediatricians, and others in health care who work with adolescents, it consolidates today's available information on this timely topic into a single convenient resource. Covers the history of the adolescent medical history and the need for an update of the biopsychosocial model, which has not significantly changed since 1977. Discusses nutrition screening, sleep screening, exercise screening, adverse childhood experiences (ACEs) screening, educational screening, behavioral and emotional screening, and more. Presents the knowledge and experience of leading experts who have assembled the most up-to-date recommendations for adolescent health screening. Explores today's knowledge of health screening and discusses future directions to ensure healthy habits in adolescents, including education and self-efficacy.
Author: Subhash C. Basak
Publisher: Elsevier
ISBN: 0323857140
Category : Science
Languages : en
Pages : 503
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Book Description
Big Data Analytics in Chemoinformatics and Bioinformatics: With Applications to Computer-Aided Drug Design, Cancer Biology, Emerging Pathogens and Computational Toxicology provides an up-to-date presentation of big data analytics methods and their applications in diverse fields. The proper management of big data for decision-making in scientific and social issues is of paramount importance. This book gives researchers the tools they need to solve big data problems in these fields. It begins with a section on general topics that all readers will find useful and continues with specific sections covering a range of interdisciplinary applications. Here, an international team of leading experts review their respective fields and present their latest research findings, with case studies used throughout to analyze and present key information. Brings together the current knowledge on the most important aspects of big data, including analysis using deep learning and fuzzy logic, transparency and data protection, disparate data analytics, and scalability of the big data domain Covers many applications of big data analysis in diverse fields such as chemistry, chemoinformatics, bioinformatics, computer-assisted drug/vaccine design, characterization of emerging pathogens, and environmental protection Highlights the considerable benefits offered by big data analytics to science, in biomedical fields and in industry
Author: Aboul Ella Hassanien
Publisher: Springer
ISBN: 331911056X
Category : Technology & Engineering
Languages : en
Pages : 502
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Book Description
This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.
Author: Pantea Keikhosrokiani
Publisher: Academic Press
ISBN: 0323985165
Category : Medical
Languages : en
Pages : 356
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Book Description
Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work. Presents theories, methods and approaches in which data analytic techniques are used for medical data Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases Discusses social, behavioral, and medical fake news analytics for medical information systems
Author: Parag Kulkarni
Publisher: PHI Learning Pvt. Ltd.
ISBN: 8120351169
Category : Language Arts & Disciplines
Languages : en
Pages : 206
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Book Description
The book is an unstructured data mining quest, which takes the reader through different features of unstructured data mining while unfolding the practical facets of Big Data. It emphasizes more on machine learning and mining methods required for processing and decision-making. The text begins with the introduction to the subject and explores the concept of data mining methods and models along with the applications. It then goes into detail on other aspects of Big Data analytics, such as clustering, incremental learning, multi-label association and knowledge representation. The readers are also made familiar with business analytics to create value. The book finally ends with a discussion on the areas where research can be explored.
Author: Hrushikesha Mohanty
Publisher: Springer
ISBN: 8132224949
Category : Computers
Languages : en
Pages : 195
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Book Description
This book is a collection of chapters written by experts on various aspects of big data. The book aims to explain what big data is and how it is stored and used. The book starts from the fundamentals and builds up from there. It is intended to serve as a review of the state-of-the-practice in the field of big data handling. The traditional framework of relational databases can no longer provide appropriate solutions for handling big data and making it available and useful to users scattered around the globe. The study of big data covers a wide range of issues including management of heterogeneous data, big data frameworks, change management, finding patterns in data usage and evolution, data as a service, service-generated data, service management, privacy and security. All of these aspects are touched upon in this book. It also discusses big data applications in different domains. The book will prove useful to students, researchers, and practicing database and networking engineers.
Author: Funmi Obembe
Publisher: SAGE Publications Limited
ISBN: 1529615925
Category : Business & Economics
Languages : en
Pages : 393
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Book Description
This practical textbook offers a hands-on introduction to big data analytics, helping you to develop the skills required to hit the ground running as a data professional. It complements theoretical foundations with an emphasis on the application of big data analytics, illustrated by real-life examples and datasets. Containing comprehensive coverage of all the key topics in this area, this book uses open-source technologies and examples in Python and Apache Spark. Learning features include: - Ethics by Design encourages you to consider data ethics at every stage. - Industry Insights facilitate a deeper understanding of the link between what you are studying and how it is applied in industry. - Datasets, questions, and exercises give you the opportunity to apply your learning. Dr Funmi Obembe is the Head of Technology at the Faculty of Arts, Science and Technology, University of Northampton. Dr Ofer Engel is a Data Scientist at the University of Groningen.
