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  • English  (5)
  • Safari, an O'Reilly Media Company.
  • MATHEMATICS ; Probability & Statistics ; General  (3)
  • Application software ; Development  (2)
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  • English  (5)
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  • 1
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Take Control Books | Boston, MA : Safari
    ISBN: 9781947282445
    Language: English
    Pages: 1 online resource (229 pages)
    Edition: 1st edition
    Keywords: Mac OS ; Application software Development ; Electronic books ; local ; Electronic books ; Mac OS ; Logiciels d'application ; Développement ; Application software ; Development
    Abstract: In macOS 10.15 Catalina, Apple finally did away with iTunes. In its place are three new apps-Music, TV, and Podcasts-with audiobooks now handled by the Books app and syncing of mobile devices handled by the Finder. Where once iTunes was an all-purpose media hub, now you may use up to five apps to accomplish the same things. The new apps also add more features (while, sadly, removing a few things too). Take Control of macOS Media Apps is your guide to this new, post-iTunes world. Kirk McElhearn, whose earlier books on iTunes 10, 11, and 12 collectively sold nearly 14,000 copies, is back with a new book that shows you how to manage your music, videos, podcasts, and audiobooks in Catalina. Whether you just want to play your media, or you want to go deeper with special features like Genius, Shuffle, Up Next, Apple Music, and iTunes Match, this comprehensive guide has the answers you need. Kirk also looks at various ways of bringing audio and video into Apple's media apps, tagging songs and videos so you can find them more easily later, creating playlists, sharing your library over a home network, and syncing media with your iPhone, iPad, or iPod. The book covers how to: Play Music: Learn the basics of playing audio (and even music videos) in the Music app. You'll also find tips on making quick playlists with Genius and Up Next, learn the best ways to search for the music you want to hear, stream music to other devices in your home, and view lyrics while tunes play. Stream Music: Use Apple Music, a paid service, to listen to any of 50 million tracks. Or listen to live broadcasts from Apple Music Radio (including Beats 1). View Your Music and Other Content: Learn how to use the sidebar, view your music library, and work with contextual menus in the Music app. Store Your Music Library in the Cloud: What are the pros and cons of Apple's Cloud Music Library? How do Music and iTunes Match figure out whether to upload your music when setting up your Cloud Music Library? You'll get answers to these questions and more. Use the iTunes Store: iTunes may be gone, but the iTunes Store is still open for business! Find tips on shopping in the iTunes Store, and get advice on sharing your purchases with family members and among your various Apple devices. Tag Your Music: Tags are bits of information (also known as "metadata") that can describe your media. Learn which tags to bother changing, the best ways to add lyrics and album art, how to rate songs with stars, ...
    Note: Online resource; Title from title page (viewed January 21, 2020) , Mode of access: World Wide Web.
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  • 2
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Chapman and Hall/CRC | Boston, MA : Safari
    ISBN: 9781482237955 , 1482237954 , 1322629536 , 9781322629537 , 042917389X , 9780429173899 , 9781482237948
    Language: English
    Pages: 1 online resource (270 pages)
    Edition: 1st edition
    Series Statement: Monographs on statistics & applied probability 139
    Parallel Title: Erscheint auch als
    Keywords: Dimensional analysis ; Multivariate analysis ; Big data ; Statistics ; Electronic books ; local ; Analyse dimensionnelle ; Analyse multivariée ; Données volumineuses ; Statistique ; statistics ; MATHEMATICS ; Applied ; MATHEMATICS ; Probability & Statistics ; General ; Big data ; Dimensional analysis ; Multivariate analysis ; Statistics ; Boosting ; Datenanalyse ; Hochdimensionale Daten ; Inferenzstatistik ; Lasso-Methode ; Mathematische Modellierung ; Statistik
    Abstract: Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise. Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for handling high-dimensional data. The book is intended to expose the reader to the key concepts and ideas in the most simple settings possible while avoiding unnecessary technicalities. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this highly accessible text: Describes the challenges related to the analysis of high-dimensional data Covers cutting-edge statistical methods including model selection, sparsity and the lasso, aggregation, and learning theory Provides detailed exercises at the end of every chapter with collaborative solutions on a wikisite Illustrates concepts with simple but clear practical examples Introduction to High-Dimensional Statistics is suitable for graduate students and researchers interested in discovering modern statistics for massive data. It can be used as a graduate text or for self-study.
    Note: Online resource; Title from title page (viewed December 17, 2014) , Mode of access: World Wide Web.
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  • 3
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : CRC Press | Boston, MA : Safari
    ISBN: 9781482204346 , 1482204347 , 9781439862636
    Language: English
    Pages: 1 online resource (362 pages)
    Edition: 1st edition
    Series Statement: The operations research series
    Parallel Title: Erscheint auch als
    Keywords: MATLAB ; Linear programming ; Mathematical optimization ; Numerical analysis Computer programs ; Electronic books ; local ; MATLAB ; Programmation linéaire ; Optimisation mathématique ; MATHEMATICS ; Applied ; MATHEMATICS ; Probability & Statistics ; General ; Linear programming ; Mathematical optimization ; Numerical analysis ; Computer programs
    Abstract: Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with MATLAB® provides a concrete and intuitive yet rigorous introduction to modern linear optimization. In addition to fundamental topics, the book discusses current linear optimization technologies such as predictor-path following interior point methods for both linear and quadratic optimization as well as the inclusion of linear optimization of uncertainty i.e. stochastic programming with recourse and robust optimization. The author introduces both stochastic programming and robust optimization as frameworks to deal with parameter uncertainty. The author's unusual approach-developing these topics in an introductory book-highlights their importance. Since most applications require decisions to be made in the face of uncertainty, the early introduction of these topics facilitates decision making in real world environments. The author also includes applications and case studies from finance and supply chain management that involve the use of MATLAB. Even though there are several LP texts in the marketplace, most do not cover data uncertainty using stochastic programming and robust optimization techniques. Most emphasize the use of MS Excel, while this book uses MATLAB which is the primary tool of many engineers, including financial engineers. The book focuses on state-of-the-art methods for dealing with parameter uncertainty in linear programming, rigorously developing theory and methods. But more importantly, the author's meticulous attention to developing intuition before presenting theory makes the material come alive.
    Note: Online resource; Title from title page (viewed September 5, 2013) , Mode of access: World Wide Web.
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  • 4
    ISBN: 0738438464 , 9780738438467
    Language: English
    Pages: 1 online resource (638 pages)
    Series Statement: IBM Redbooks
    Parallel Title: Erscheint auch als
    DDC: 005.376
    Keywords: WebSphere ; Computational grids (Computer systems) ; Application software Development ; Client/server computing ; Web servers Computer programs ; Electronic books ; local ; WebSphere ; WebSphere ; Electrical & Computer Engineering ; Engineering & Applied Sciences ; Telecommunications ; Grilles informatiques ; Logiciels d'application ; Développement ; Architecture client-serveur (Informatique) ; Serveurs Web ; Logiciels ; Application software ; Development ; Client/server computing ; Computational grids (Computer systems) ; Web servers ; Computer programs
    Abstract: This IBM® Redbooks® publication provides information about the concepts, planning, and design of IBM WebSphere® Application Server V8.5 environments. The target audience of this book is IT architects and consultants who want more information about the planning and design of application-serving environments, from small to large, and complex implementations. This book addresses the packaging and features in WebSphere Application Server V8.5, and highlights the most common implementation topologies. It provides information about planning for specific tasks and components that conform to the WebSphere Application Server environment. Also in this book are planning guidelines for Websphere Application Server V8.5 and Websphere Application Server Network Deployment V8.5 on distributed platforms. It also includes guidelines for WebSphere Application Server for IBM z/OS® V8.5. This book contains information about migration considerations when moving from previous releases. Please note that the additional material referenced in the text is not available from IBM.
    Note: Online resource; Title from title page (viewed June 25, 2012) , Mode of access: World Wide Web.
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  • 5
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : CRC Press | Boston, MA : Safari
    ISBN: 9781466592216 , 1466592214 , 9781439885017
    Language: English
    Pages: 1 online resource (557 pages)
    Edition: 1st edition
    Parallel Title: Erscheint auch als
    Keywords: Geography Data processing ; Geography Statistical methods ; Environmental sciences Data processing ; Environmental sciences Statistical methods ; Engineering Data processing ; Engineering Statistical methods ; Electronic books ; local ; Géographie ; Informatique ; Géographie ; Méthodes statistiques ; Sciences de l'environnement ; Informatique ; Sciences de l'environnement ; Méthodes statistiques ; Ingénierie ; Informatique ; Ingénierie ; Méthodes statistiques ; MATHEMATICS ; Applied ; MATHEMATICS ; Probability & Statistics ; General ; Engineering ; Data processing ; Engineering ; Statistical methods ; Environmental sciences ; Data processing ; Environmental sciences ; Statistical methods ; Geography ; Data processing ; Geography ; Statistical methods
    Abstract: Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustainability, the book brings together principles of statistics and probability, multivariate analysis, and spatial analysis methods applicable across a variety of science and engineering disciplines. Learn How to Use a Variety of Data Analysis and Statistics Methods Based on the author's many years of teaching graduate and undergraduate students, this textbook emphasizes hands-on learning. Organized into two parts, it allows greater flexibility using the material in various countries and types of curricula. The first part covers probability, random variables and inferential statistics, applications of regression, time series analysis, and analysis of spatial point patterns. The second part uses matrix algebra to address multidimensional problems. After a review of matrices, it delves into multiple regression, dependent random processes and autoregressive time series, spatial analysis using geostatistics and spatial regression, discriminant analysis, and a variety of multivariate analyses based on eigenvector methods. Build from Fundamental Concepts to Effective Problem Solving Each chapter starts with conceptual and theoretical material to give a firm foundation in how the methods work. Examples and exercises illustrate the applications and demonstrate how to go from concepts to problem solving. Hands-on computer sessions allow students to grasp the practical implications and learn by doing. Throughout, the computer examples and exercises use seeg and RcmdrPlugin.seeg , open-source R packages developed by the author, which help students acquire the skills to implement and conduct analysis and to analyze the results. This self-contained book offers a unified presentation of data analysis methods for more effective problem solving. With clear, easy-to-follow explanations, the book helps students to develop a solid understanding of basic statistical analysis and prepares them for learning the more advanced and specialized methods they will need in their work.
    Note: Online resource; Title from title page (viewed December 7, 2012) , Mode of access: World Wide Web.
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