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  • Big Data and Social Science

    Data Science Methods and Tools for Research and Practice

    Series series Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences
    ***Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition***shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern ... Leer más

    $84.99 USD

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  • Making Software

    What Really Works, and Why We Believe It

    Many claims are made about how certain tools, technologies, and practices improve software development. But which claims are verifiable, and which are merely wishful thinking? In this book, leading thinkers such as Steve McConnell, Barry Boehm, and Barbara Kitchenham offer essays that uncover the truth and unmask myths commonly held among the software development community. Their insights may ... Leer más

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  • Operational Risk Management

    A Practical Approach to Intelligent Data Analysis

    Edición de Yossi Raanan, Ron S. Kenett ...
    Series Libro 106 - Statistics in Practice
    Models and methods for operational risks assessment and mitigation are gaining importance in financial institutions, healthcare organizations, industry, businesses and organisations in general. This book introduces modern Operational Risk Management and describes how various data sources of different types, both numeric and semantic sources such as text can be integrated and analyzed. The book ... Leer más

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  • Automating Open Source Intelligence

    Algorithms for OSINT

    Algorithms for Automating Open Source Intelligence (OSINT) presents information on the gathering of information and extraction of actionable intelligence from openly available sources, including news broadcasts, public repositories, and more recently, social media. As OSINT has applications in crime fighting, state-based intelligence, and social research, this book provides recent advances in text ... Leer más

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  • Privacy, Big Data, and the Public Good

    Frameworks for Engagement

    Massive amounts of data on human beings can now be analyzed. Pragmatic purposes abound, including selling goods and services, winning political campaigns, and identifying possible terrorists. Yet 'big data' can also be harnessed to serve the public good: scientists can use big data to do research that improves the lives of human beings, improves government services, and reduces taxpayer costs. In ... Leer más

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  • Urban Analytics

    Series series Spatial Analytics and GIS
    The economic and political situation of cities has shifted in recent years in light of rapid growth amidst infrastructure decline, the suburbanization of poverty and inner city revitalization. At the same time, the way that data are used to understand urban systems has changed dramatically.Urban Analytics offers a field-defining look at the challenges and opportunities of using new and emerging ... Leer más

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  • Handbook of Data Quality

    Research and Practice

    Edición de Shazia Sadiq ...
    Series series Computer Science (R0)
    The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals ... Leer más

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  • Web and Network Data Science

    Modeling Techniques in Predictive Analytics

    de Thomas Miller ...
    Series series FT Press Analytics
    Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics.Some books in this field focus either entirely on business issues (e.g ... Leer más

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  • Statistics for Data Science

    Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks

    Get your statistics basics right before diving into the world of data science Key FeaturesNo need to take a degree in statistics, read this book and get a strong statistics base for data science and real-world programs;Implement statistics in data science tasks such as data cleaning, mining, and analysisLearn all about probability, statistics, numerical computations, and more with the help of R ... Leer más

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  • Privacy in Social Networks

    Series series Synthesis Lectures on Data Mining and Knowledge Discovery
    This synthesis lecture provides a survey of work on privacy in online social networks (OSNs). This work encompasses concerns of users as well as service providers and third parties. Our goal is to approach such concerns from a computer-science perspective, and building upon existing work on privacy, security, statistical modeling and databases to provide an overview of the technical and ... Leer más

    $32.99 USD

  • Data Mining Applications with R

    Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. ... Leer más

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  • Statistical Methods for Recommender Systems

    Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect ... Leer más

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