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Understanding Complex Datasets
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Book Synopsis Understanding Complex Datasets by : David Skillicorn
Download or read book Understanding Complex Datasets written by David Skillicorn and published by CRC Press. This book was released on 2007-05-17 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Mining of Massive Datasets by : Jure Leskovec
Download or read book Mining of Massive Datasets written by Jure Leskovec and published by Cambridge University Press. This book was released on 2014-11-13 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
Book Synopsis The Focal Encyclopedia of Photography by : Michael R. Peres
Download or read book The Focal Encyclopedia of Photography written by Michael R. Peres and published by Taylor & Francis. This book was released on 2013-05-29 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: *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)
Book Synopsis Complex Datasets and Inverse Problems by : Regina Y. Liu
Download or read book Complex Datasets and Inverse Problems written by Regina Y. Liu and published by IMS. This book was released on 2007 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Robson Leonardo Ferreira Cordeiro Publisher :Springer Science & Business Media ISBN 13 :1447148908 Total Pages :124 pages Book Rating :4.4/5 (471 download)
Book Synopsis Data Mining in Large Sets of Complex Data by : Robson Leonardo Ferreira Cordeiro
Download or read book Data Mining in Large Sets of Complex Data written by Robson Leonardo Ferreira Cordeiro and published by Springer Science & Business Media. This book was released on 2013-01-11 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount and the complexity of the data gathered by current enterprises are increasing at an exponential rate. Consequently, the analysis of Big Data is nowadays a central challenge in Computer Science, especially for complex data. For example, given a satellite image database containing tens of Terabytes, how can we find regions aiming at identifying native rainforests, deforestation or reforestation? Can it be made automatically? Based on the work discussed in this book, the answers to both questions are a sound “yes”, and the results can be obtained in just minutes. In fact, results that used to require days or weeks of hard work from human specialists can now be obtained in minutes with high precision. Data Mining in Large Sets of Complex Data discusses new algorithms that take steps forward from traditional data mining (especially for clustering) by considering large, complex datasets. Usually, other works focus in one aspect, either data size or complexity. This work considers both: it enables mining complex data from high impact applications, such as breast cancer diagnosis, region classification in satellite images, assistance to climate change forecast, recommendation systems for the Web and social networks; the data are large in the Terabyte-scale, not in Giga as usual; and very accurate results are found in just minutes. Thus, it provides a crucial and well timed contribution for allowing the creation of real time applications that deal with Big Data of high complexity in which mining on the fly can make an immeasurable difference, such as supporting cancer diagnosis or detecting deforestation.
Book Synopsis Algorithms and Data Structures for Massive Datasets by : Dzejla Medjedovic
Download or read book Algorithms and Data Structures for Massive Datasets written by Dzejla Medjedovic and published by Simon and Schuster. This book was released on 2022-08-16 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Geographic Data Mining and Knowledge Discovery by : Harvey J. Miller
Download or read book Geographic Data Mining and Knowledge Discovery written by Harvey J. Miller and published by CRC Press. This book was released on 2009-05-27 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and geovisualization (GVis) have been developed. In addition, there has bee
Book Synopsis Learning from Complex Datasets by : Geoffrey J. McLachlan
Download or read book Learning from Complex Datasets written by Geoffrey J. McLachlan and published by Wiley-Blackwell. This book was released on 2012-02-24 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides insight and advice on the most appropriate and effective statistical methods to employ when using large or robust data. It covers the handling of high-dimensional data and data in which there is bias in the type collected and presents applications in modern and molecular genetics to showcase the most challenging datasets. In addition, it features full-color art throughout the book to illustrate the importance of color in data understanding and interpretation and offers access to a dedicated author web site.
Book Synopsis artificial Intelligence / Machine Learning In Marketing by : James Seligman
Download or read book artificial Intelligence / Machine Learning In Marketing written by James Seligman and published by Lulu.com. This book was released on 2020-02-17 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theory and practice of AI and ML in marketing saving time, money
Book Synopsis Using Secondary Datasets to Understand Persons with Developmental Disabilities and their Families by :
Download or read book Using Secondary Datasets to Understand Persons with Developmental Disabilities and their Families written by and published by Academic Press. This book was released on 2013-10-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 :Nadia Magnenat-Thalmann Publisher :Springer Science & Business Media ISBN 13 :3642104681 Total Pages :238 pages Book Rating :4.6/5 (421 download)
Book Synopsis Modelling the Physiological Human by : Nadia Magnenat-Thalmann
Download or read book Modelling the Physiological Human written by Nadia Magnenat-Thalmann and published by Springer Science & Business Media. This book was released on 2009-11-17 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Materials Informatics and Catalysts Informatics by : Keisuke Takahashi
Download or read book Materials Informatics and Catalysts Informatics written by Keisuke Takahashi and published by Springer Nature. This book was released on with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis From Theory to Practice Machine Learning Techniques for Clustering and Segmentation in Data Science for Engineers by : Thiago Jace
Download or read book From Theory to Practice Machine Learning Techniques for Clustering and Segmentation in Data Science for Engineers written by Thiago Jace and published by . This book was released on 2023-12-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the Importance of Clustering and Segmentation in Data ScienceIn the ever-evolving field of data science, engineers are constantly seeking innovative techniques to extract meaningful insights from vast amounts of data. One such technique that has gained significant popularity is clustering and segmentation. In this subchapter, we will dive deep into the importance of clustering and segmentation in data science and its applications within the niche of machine learning for data science. Clustering, in its essence, involves grouping similar data points together based on their inherent characteristics. By identifying patterns and relationships among data points, clustering enables engineers to uncover hidden structures within the data, leading to valuable insights. With the ability to handle large datasets efficiently, clustering has become an indispensable tool for engineers working on data science projects. Segmentation, on the other hand, takes clustering a step further by partitioning data into distinct subsets or segments. This process allows engineers to understand the heterogeneous nature of the data and tailor their analysis and decision-making accordingly. By segmenting data, engineers are able to identify specific target groups, understand their unique preferences, and devise personalized strategies that drive business growth and enhance customer satisfaction. The importance of clustering and segmentation in data science cannot be overstated. These techniques enable engineers to gain a comprehensive understanding of complex datasets, identify trends, and make data-driven decisions with confidence. Whether it is customer segmentation for targeted marketing campaigns, anomaly detection in cybersecurity, or analyzing patterns in healthcare data, clustering and segmentation play a vital role in extracting valuable insights that drive business success. Furthermore, with the advent of machine learning algorithms and techniques, clustering and segmentation have witnessed significant advancements. Engineers can now employ sophisticated algorithms such as k-means, hierarchical clustering, and density-based clustering to achieve more accurate results and handle complex datasets effectively. These advancements have opened up new avenues for innovation and application of clustering and segmentation techniques in various industries, including finance, healthcare, retail, and more.
Download or read book Music Data Mining written by Tao Li and published by CRC Press. This book was released on 2011-07-12 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to successfully employ data mining techniques for the purpose of music processing. The book first covers music data mining tasks and algorithms and audio feature extraction, providing a framework for subsequent chapters. With a focus on data classification, it then describes a computational approach inspired by human auditory perception and examines instrument recognition, the effects of music on moods and emotions, and the connections between power laws and music aesthetics. Given the importance of social aspects in understanding music, the text addresses the use of the Web and peer-to-peer networks for both music data mining and evaluating music mining tasks and algorithms. It also discusses indexing with tags and explains how data can be collected using online human computation games. The final chapters offer a balanced exploration of hit song science as well as a look at symbolic musicology and data mining. The multifaceted nature of music information often requires algorithms and systems using sophisticated signal processing and machine learning techniques to better extract useful information. An excellent introduction to the field, this volume presents state-of-the-art techniques in music data mining and information retrieval to create novel ways of interacting with large music collections.
Book Synopsis Computational Intelligent Data Analysis for Sustainable Development by : Ting Yu
Download or read book Computational Intelligent Data Analysis for Sustainable Development written by Ting Yu and published by CRC Press. This book was released on 2016-04-19 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development present
Book Synopsis Data Science and Analytics with Python by : Jesus Rogel-Salazar
Download or read book Data Science and Analytics with Python written by Jesus Rogel-Salazar and published by CRC Press. This book was released on 2018-02-05 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main concepts used in data science using tools developed in Python, such as SciKit-learn, Pandas, Numpy, and others. The use of Python is of particular interest, given its recent popularity in the data science community. The book can be used by seasoned programmers and newcomers alike. The book is organized in a way that individual chapters are sufficiently independent from each other so that the reader is comfortable using the contents as a reference. The book discusses what data science and analytics are, from the point of view of the process and results obtained. Important features of Python are also covered, including a Python primer. The basic elements of machine learning, pattern recognition, and artificial intelligence that underpin the algorithms and implementations used in the rest of the book also appear in the first part of the book. Regression analysis using Python, clustering techniques, and classification algorithms are covered in the second part of the book. Hierarchical clustering, decision trees, and ensemble techniques are also explored, along with dimensionality reduction techniques and recommendation systems. The support vector machine algorithm and the Kernel trick are discussed in the last part of the book. About the Author Dr. Jesús Rogel-Salazar is a Lead Data scientist with experience in the field working for companies such as AKQA, IBM Data Science Studio, Dow Jones and others. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK, He obtained his doctorate in physics at Imperial College London for work on quantum atom optics and ultra-cold matter. He has held a position as senior lecturer in mathematics as well as a consultant in the financial industry since 2006. He is the author of the book Essential Matlab and Octave, also published by CRC Press. His interests include mathematical modelling, data science, and optimization in a wide range of applications including optics, quantum mechanics, data journalism, and finance.
Book Synopsis Hacking: The Art of Exploitation, 2nd Edition by : Jon Erickson
Download or read book Hacking: The Art of Exploitation, 2nd Edition written by Jon Erickson and published by No Starch Press. This book was released on 2008-02-01 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hacking is the art of creative problem solving, whether that means finding an unconventional solution to a difficult problem or exploiting holes in sloppy programming. Many people call themselves hackers, but few have the strong technical foundation needed to really push the envelope. Rather than merely showing how to run existing exploits, author Jon Erickson explains how arcane hacking techniques actually work. To share the art and science of hacking in a way that is accessible to everyone, Hacking: The Art of Exploitation, 2nd Edition introduces the fundamentals of C programming from a hacker's perspective. The included LiveCD provides a complete Linux programming and debugging environment—all without modifying your current operating system. Use it to follow along with the book's examples as you fill gaps in your knowledge and explore hacking techniques on your own. Get your hands dirty debugging code, overflowing buffers, hijacking network communications, bypassing protections, exploiting cryptographic weaknesses, and perhaps even inventing new exploits. This book will teach you how to: – Program computers using C, assembly language, and shell scripts – Corrupt system memory to run arbitrary code using buffer overflows and format strings – Inspect processor registers and system memory with a debugger to gain a real understanding of what is happening – Outsmart common security measures like nonexecutable stacks and intrusion detection systems – Gain access to a remote server using port-binding or connect-back shellcode, and alter a server's logging behavior to hide your presence – Redirect network traffic, conceal open ports, and hijack TCP connections – Crack encrypted wireless traffic using the FMS attack, and speed up brute-force attacks using a password probability matrix Hackers are always pushing the boundaries, investigating the unknown, and evolving their art. Even if you don't already know how to program, Hacking: The Art of Exploitation, 2nd Edition will give you a complete picture of programming, machine architecture, network communications, and existing hacking techniques. Combine this knowledge with the included Linux environment, and all you need is your own creativity.
