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Author: David Skillicorn
Publisher: CRC Press
ISBN: 9781584888338
Category : Computers
Languages : en
Pages : 260
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Book Description
Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a broad range of application areas. Without having to understand every mathematical detail, the book helps you determine which matrix is appropriate for your dataset and what the results mean. Explaining the effectiveness of matrices as data analysis tools, the book illustrates the ability of matrix decompositions to provide more powerful analyses and to produce cleaner data than more mainstream techniques. The author explores the deep connections between matrix decompositions and structures within graphs, relating the PageRank algorithm of Google's search engine to singular value decomposition. He also covers dimensionality reduction, collaborative filtering, clustering, and spectral analysis. With numerous figures and examples, the book shows how matrix decompositions can be used to find documents on the Internet, look for deeply buried mineral deposits without drilling, explore the structure of proteins, detect suspicious emails or cell phone calls, and more. Concentrating on data mining mechanics and applications, this resource helps you model large, complex datasets and investigate connections between standard data mining techniques and matrix decompositions.
Author: David Skillicorn
Publisher: CRC Press
ISBN: 9781584888338
Category : Computers
Languages : en
Pages : 260
Get Book
Book Description
Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a broad range of application areas. Without having to understand every mathematical detail, the book helps you determine which matrix is appropriate for your dataset and what the results mean. Explaining the effectiveness of matrices as data analysis tools, the book illustrates the ability of matrix decompositions to provide more powerful analyses and to produce cleaner data than more mainstream techniques. The author explores the deep connections between matrix decompositions and structures within graphs, relating the PageRank algorithm of Google's search engine to singular value decomposition. He also covers dimensionality reduction, collaborative filtering, clustering, and spectral analysis. With numerous figures and examples, the book shows how matrix decompositions can be used to find documents on the Internet, look for deeply buried mineral deposits without drilling, explore the structure of proteins, detect suspicious emails or cell phone calls, and more. Concentrating on data mining mechanics and applications, this resource helps you model large, complex datasets and investigate connections between standard data mining techniques and matrix decompositions.
Author: Jure Leskovec
Publisher: Cambridge University Press
ISBN: 1107077230
Category : Computers
Languages : en
Pages : 480
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Book Description
Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
Author: Michael R. Peres
Publisher: Taylor & Francis
ISBN: 1136106146
Category : Photography
Languages : en
Pages : 880
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Book Description
*Searchable CD ROM containing the entire book (including images) *Over 450 color images, plus never before published images provided by the George Eastman House collection, as well as images from Ansel Adams, Howard Schatz, and Jerry Uelsmann to name just a few The role and value of the picture cannot be matched for accuracy or impact. This comprehensive treatise, featuring the history and historical processes of photography, contemporary applications, and the new and evolving digital technologies, will provide the most accurate technical synopsis of the current, as well as early worlds of photography ever compiled. This Encyclopedia, produced by a team of world renown practicing experts, shares in highly detailed descriptions, the core concepts and facts relative to anything photographic. This Fourth edition of the Focal Encyclopedia serves as the definitive reference for students and practitioners of photography worldwide, expanding on the award winning 3rd edition. In addition to Michael Peres (Editor in Chief), the editors are: Franziska Frey (Digital Photography), J. Tomas Lopez (Contemporary Issues), David Malin (Photography in Science), Mark Osterman (Process Historian), Grant Romer (History and the Evolution of Photography), Nancy M. Stuart (Major Themes and Photographers of the 20th Century), and Scott Williams (Photographic Materials and Process Essentials)
Author: Donald L. Fisher
Publisher: CRC Press
ISBN: 1351979809
Category : Computers
Languages : en
Pages : 548
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Book Description
Handbook of Human Factors for Automated, Connected, and Intelligent Vehicles Subject Guide: Ergonomics & Human Factors Automobile crashes are the seventh leading cause of death worldwide, resulting in over 1.25 million deaths yearly. Automated, connected, and intelligent vehicles have the potential to reduce crashes significantly, while also reducing congestion, carbon emissions, and increasing accessibility. However, the transition could take decades. This new handbook serves a diverse community of stakeholders, including human factors researchers, transportation engineers, regulatory agencies, automobile manufacturers, fleet operators, driving instructors, vulnerable road users, and special populations. It provides information about the human driver, other road users, and human–automation interaction in a single, integrated compendium in order to ensure that automated, connected, and intelligent vehicles reach their full potential. Features Addresses four major transportation challenges—crashes, congestion, carbon emissions, and accessibility—from a human factors perspective Discusses the role of the human operator relevant to the design, regulation, and evaluation of automated, connected, and intelligent vehicles Offers a broad treatment of the critical issues and technological advances for the designing of transportation systems with the driver in mind Presents an understanding of the human factors issues that are central to the public acceptance of these automated, connected, and intelligent vehicles Leverages lessons from other domains in understanding human interactions with automation Sets the stage for future research by defining the space of unexplored questions
Author: Keisuke Takahashi
Publisher: Springer Nature
ISBN: 9819702178
Category :
Languages : en
Pages : 301
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Book Description
Author: James Seligman
Publisher: Lulu.com
ISBN: 0244563888
Category : Computers
Languages : en
Pages : 252
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Book Description
The theory and practice of AI and ML in marketing saving time, money
Author:
Publisher: Academic Press
ISBN: 0124078915
Category : Medical
Languages : en
Pages : 392
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Book Description
International Review of Research in Developmental Disabilities is an ongoing scholarly look at research into the causes, effects, classification systems, syndromes, etc. of developmental disabilities. Contributors come from wide-ranging perspectives, including genetics, psychology, education, and other health and behavioral sciences. Provides the most recent scholarly research in the study of developmental disabilities A vast range of perspectives is offered, and many topics are covered An excellent resource for academic researchers
Author: Dzejla Medjedovic
Publisher: Simon and Schuster
ISBN: 1638356564
Category : Computers
Languages : en
Pages : 302
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Book Description
Massive modern datasets make traditional data structures and algorithms grind to a halt. This fun and practical guide introduces cutting-edge techniques that can reliably handle even the largest distributed datasets. In Algorithms and Data Structures for Massive Datasets you will learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects—and there’s no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you’ll find the sweet spot of saving space without sacrificing your data’s accuracy. About the technology Standard algorithms and data structures may become slow—or fail altogether—when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost. This unique book distills cutting-edge research papers into practical techniques for sketching, streaming, and organizing massive datasets on-disk and in the cloud. About the book Algorithms and Data Structures for Massive Datasets introduces processing and analytics techniques for large distributed data. Packed with industry stories and entertaining illustrations, this friendly guide makes even complex concepts easy to understand. You’ll explore real-world examples as you learn to map powerful algorithms like Bloom filters, Count-min sketch, HyperLogLog, and LSM-trees to your own use cases. What's inside Probabilistic sketching data structures Choosing the right database engine Designing efficient on-disk data structures and algorithms Algorithmic tradeoffs in massive-scale systems Computing percentiles with limited space resources About the reader Examples in Python, R, and pseudocode. About the author Dzejla Medjedovic earned her PhD in the Applied Algorithms Lab at Stony Brook University, New York. Emin Tahirovic earned his PhD in biostatistics from University of Pennsylvania. Illustrator Ines Dedovic earned her PhD at the Institute for Imaging and Computer Vision at RWTH Aachen University, Germany. Table of Contents 1 Introduction PART 1 HASH-BASED SKETCHES 2 Review of hash tables and modern hashing 3 Approximate membership: Bloom and quotient filters 4 Frequency estimation and count-min sketch 5 Cardinality estimation and HyperLogLog PART 2 REAL-TIME ANALYTICS 6 Streaming data: Bringing everything together 7 Sampling from data streams 8 Approximate quantiles on data streams PART 3 DATA STRUCTURES FOR DATABASES AND EXTERNAL MEMORY ALGORITHMS 9 Introducing the external memory model 10 Data structures for databases: B-trees, Bε-trees, and LSM-trees 11 External memory sorting
Author: Information Today Inc
Publisher: Information Today, Inc.
ISBN: 9781573872423
Category : Computers
Languages : en
Pages : 632
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Book Description
ARIST, published annually since 1966, is a landmark publication within the information science community. It surveys the landscape of information science and technology, providing an analytical, authoritative, and accessible overview of recent trends and significant developments. The range of topics varies considerably, reflecting the dynamism of the discipline and the diversity of theoretical and applied perspectives. While ARIST continues to cover key topics associated with "classical" information science (e.g., bibliometrics, information retrieval), editor Blaise Cronin is selectively expanding its footprint in an effort to connect information science more tightly with cognate academic and professional communities. Contents of Volume 40 (2006): SECTION I: Information and Society Chapter 1: The Micro- and Macroeconomics of Information, Sandra Braman Chapter 2: The Geographies of the Internet, Matthew Zook Chapter 3: Open Access, M. Carl Drott SECTION II: Technologies and Systems Chapter 4: TREC: An Overview, Donna K. Harman and Ellen M. Voorhees Chapter 5: Semantic Relations in Information Science, Christopher S. G. Khoo and Jin-Cheon Na Chapter 6: Intelligence and Security Informatics, Hsinchun Chen and Jennifer Xu SECTION III: Information Needs and Use Chapter 7: Information Behavior, Donald O. Case Chapter 8: Collaborative Information Seeking and Retrieval, Jonathan Foster Chapter 9: Information Failures in Health Care, Anu MacIntosh-Murray and Chun Wei Choo Chapter 10: Workplace Studies and Technological Change, Angela Cora Garcia, Mark E. Dawes, Mary Lou Kohne, Felicia Miller, and Stephan F. Groschwitz SECTION IV: Theoretical Perspectives Chapter 11: Information History, Alistair Black Chapter 12: Social Epistemology and Information Science, Don Fallis Chapter 13: Formal Concept Analysis in Information Science, Uta Priss.
Author: Nadia Magnenat-Thalmann
Publisher: Springer Science & Business Media
ISBN: 3642104681
Category : Computers
Languages : en
Pages : 238
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Book Description
This book constitutes the proceedings of the Second 3D Physiological Human Workshop, 3DPH 2009, held in Zermatt, Switzerland, in November/December 2009. The 19 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on Segmentation, Anatomical and Physiological Modelling, Simulation Models, Motion Analysis, Medical Visualization and Interaction, as well as Medical Ontology.
