data science 2018
This timely and multifaceted book is concerned with the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the ensuing systemic outcomes pertaining to sustainability as informed and underpinned by data -driven
Radio frequency identification: A new opportunity for data science
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Abstract Radio Frequency Identification (RFID) has taken center stage at retail and consumer products forum. RFID is not a new technology; it has been in use for many years. In this paper, we first review RFID technology and the components that form the backbone of
Teaching data science to secondary students: The mobilize introduction to data science curriculum
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Making sense of data is complex, and the knowledge and skills required to understand Big Data -and many open data sources-go beyond those taught in traditional introductory statistics courses. The Mobilize project has created and implemented a course for secondary
Data Science
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Data science is a fast-growing science, technology, engineering, and mathematics (STEM) field that spans areas of computing, statistics, and operations research to drive business value. Business analytics is concerned with the process of transforming data into insights for In early 201 the three editors of this volume were instrumental in founding the ZHAW Datalab, a Data Science Research Institute (DSRI) 1 at Zurich University of Applied Sciences. 2 Big data was big in the public press, 3 but DSRIs were still rare, especially in
Data science and data scientist
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? Data Science is an interdisciplinary field about processes and systems to extract knowledge or insights from large volumes of data in various forms either structured or unstructured, which is a continuation of some of the data analysis fields such as data mining This book is intended for professionals working in Transportation who wish to add Data Science skills to their work, and for current or potential future students of graduate or advanced undergraduate Transport Studies building skills to work in the profession. It is
Data science : professional requirements and competence evaluation
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The paper discusses the contemporary approach to structure of Data Science understanding in the sense of professional requirements, skills and competences for Data Science professionals. The roles of such fields as statistics, data mining, and predictive analytics are
Data science , artificial intelligence and the futures of work
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This document presents a review of existing literature on the future of work. This review has been commissioned by The Alan Turing Institute to inform the Turing research strategy aiming to further data science and artificial intelligence (AI) research to address real-world
Big data and data science in health care: What nurses and midwives need to know
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The evolution of technology in contemporary society has been accelerating in recent decades, with smaller, more interconnected hardware devices and software applications becoming the norm. As desktop computing paved the way for mobile platforms, which are
Preface: intelligent techniques for data science
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With the extraordinary spread of computers and sensors, enormous amounts of data are generated every day in a range of areas search engines, social media, healthcare organizations, insurance companies, financial industry, retail, and many others. Data
Data Science : The End of Statistics
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Page 1. Data Science : The End of Statistics Larry Wasserman Carnegie Mellon University Interface 2015 Page 2. Conclusion Page 3. Conclusion Lets turn the Interface meeting into the statistics version of NIPS Page 4. This Talk Page 5. This Talk Will be short Page 6. This Talk Page 23
Doubling Pharma Value with Data Science
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The digital era is revolutionizing the health care industry, but pharmas approach to product development and market access has remained relatively unchanged. Pharma companies have been experimenting with digital technologies and analytics-driven pilots, but instead of
Data Science : Bigtable, Mapreduce and Google File System
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Data science is the extension of research findings and drawing conclusions from data . BigTable is built on a few of Google technologies . MapReduce is a programming model and an associated implementation for processing and generating large data sets with a
Mathematical Issues in Data Science and Applications for Health care
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For development in military applications, industrial and government the predictive analytics and decision models have long been cornerstones. In modern healthcare system technologies and big data analytics and modeling of multi-source data system play an
Ten lectures and forty-two open problems in the mathematics of data science
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These are notes from a course I gave at MIT on the Fall of 2015 entitled: 18. S096: Topics in Mathematics of Data Science . These notes are not in final form and will be continuously edited and/or corrected (as I am sure they contain many typos). Please use at your own risk
Data science for business
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Page 1. Data Science for Business Foster Provost and Tom Fawcett Beijing Cambridge Farnham Koln Sebastopol Tokyo Page 2. Table of Contents Preface xiii 1. Introduction: Data -Analytic Thinking 1 The Ubiquity of Data Opportunities 1 Example: Hurricane Frances
Data Science
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Fulfilling this data science promise also means more accurate tracking, which results in better return on advertising investment (ROI), and ad spending (ROAS). With improved accuracy, hotel marketers can be more confident in their work. These stronger returns canWe argue that the data integration (DI) community should devote far more effort to building systems, in order to truly advance the field. We discuss the limitations of current DI systems, and point out that there is already an existing popular DI system out there, which is PyData
Issues and challenges in convergence of big data , cloud and data science
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ABSTRACT Big data , Cloud Computing and Data Science are currently trending in organizations across the globe. Big Data refers to technologies and techniques that involve data that is massive, heterogeneous and fast-changing for conventional technologies, skills CSE PROJECTS