High Performance Data Mining
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High Performance Data Mining And Big Data Analytics
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Author : Khosrow Hassibi
language : en
Publisher: Createspace Independent Pub
Release Date : 2014-10-07
High Performance Data Mining And Big Data Analytics written by Khosrow Hassibi and has been published by Createspace Independent Pub this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-07 with Technology & Engineering categories.
The use of machine learning and data mining to create value from corporate or public data is nothing new. It is not the first time that these technologies are in the spotlight. Many remember the late '80s and the early '90s when machine learning techniques—in particular neural networks—had become very popular. Data mining was at a rise. There were talks everywhere about advanced analysis of data for decision making. Even the popular android character in “Star Trek: The Next Generation” had been named appropriately as “Data.” Data mining science has been the cornerstone of many data products and applications for more than two decades, e.g., in finance and retail. Credit scores have been in use for decades to assess credit worthiness of people when applying for credit or loan. Sophisticated real-time fraud scores based on individual's transaction spending patterns have been used since early '90s to protect credit card holders from a variety of fraud schemes. However, the popularity of web products from the likes of Google, Linked-in, Amazon, and Facebook has helped analytics become a household name. While a decade ago, the masses did not know how their detailed data were being used by corporations for decision making, today they are fully aware of that fact. Many people, especially the millennial generation, voluntarily provide detailed information about themselves. Today people know that any mouse click they generate, any comment they write, any transaction they perform, and any location they go to, may be captured and analyzed for some business purpose. Every new technology comes with lots of hype and many new buzzwords. Often, fact and fiction get mixed-up making it impossible for outsiders to assess the technology's true relevance. I wrote this book to provide an objective view of analytics trends today. I have written it in complete independence, and solely as a personal passion. As a result, the views expressed in this book are those of the author and do not necessarily represent the views of, and should not be attributed to, any vendor or employer.Due to the exponential growth of data, today there is an ever increasing need to process and analyze big data. High-performance computing architectures have been devised to address the need for handling big data, not only from a transaction processing standpoint but also from a tactical and strategic analytics viewpoint. The success of big data analytics in large web companies has created a rush toward understanding the impact of new big data technologies in classic analytics environments that already employ a multitude of legacy analytics technologies. There is a wide variety of readings about big data, high-performance computing for analytics, massively parallel processing (MPP) databases, Hadoop and its ecosystem, algorithms for big data, in-memory databases, implementation of machine learning algorithms for big data platforms, and big data analytics. However, none of these readings provides an overview of these topics in a single document. The objective of this book is to provide a historical and comprehensive view of the recent trend toward high-performance computing technologies, especially as it relates to big data analytics and high-performance data mining. The book also emphasizes the impact of big data on requiring a rethinking of every aspect of the analytics life cycle, from data management, to data mining and analysis, to deployment.As a result of interactions with different stakeholders in classic organizations, I realized there was a need for a more holistic view of big data analytics' impact across classic organizations, and also the impact of high-performance computing techniques on legacy data mining. Whether you are an executive, manager, data scientist, analyst, sales or IT staff, the holistic and broad overview provided in the book will help in grasping the important topics in big data analytics and its potential impact in your organizations.
High Performance Data Mining
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Author : Yike Guo
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-08
High Performance Data Mining written by Yike Guo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-08 with Computers categories.
High Performance Data Mining: Scaling Algorithms, Applications and Systems brings together in one place important contributions and up-to-date research results in this fast moving area. High Performance Data Mining: Scaling Algorithms, Applications and Systems serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
High Performance Data Mining
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Author : Yike Guo
language : en
Publisher:
Release Date : 2014-01-15
High Performance Data Mining written by Yike Guo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Scalable High Performance Computing For Knowledge Discovery And Data Mining
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Author : Paul Stolorz
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Scalable High Performance Computing For Knowledge Discovery And Data Mining written by Paul Stolorz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Scalable High Performance Computing for Knowledge Discovery and Data Mining brings together in one place important contributions and up-to-date research results in this fast moving area. Scalable High Performance Computing for Knowledge Discovery and Data Mining serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
High Performance Data Mining Using Bio Inspired Techniques
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Author : Gianluigi Folino
language : en
Publisher:
Release Date : 2010
High Performance Data Mining Using Bio Inspired Techniques written by Gianluigi Folino and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Special Issue On High Performance Data Mining
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Author :
language : en
Publisher:
Release Date : 2001
Special Issue On High Performance Data Mining written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Data mining categories.
Powerful Database Support For High Performance Data Mining
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Author : Christian Böhm
language : en
Publisher:
Release Date :
Powerful Database Support For High Performance Data Mining written by Christian Böhm and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
High Performance Computing For Big Data
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Author : Chao Wang
language : en
Publisher: CRC Press
Release Date : 2017-10-16
High Performance Computing For Big Data written by Chao Wang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-16 with Computers categories.
High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life science, neural networks, and neuromorphic engineering. The book is organized into two main sections. The first section covers Big Data architectures, including cloud computing systems, and heterogeneous accelerators. It also covers emerging 3D IC design principles for memory architectures and devices. The second section of the book illustrates emerging and practical applications of Big Data across several domains, including bioinformatics, deep learning, and neuromorphic engineering. Features Covers a wide range of Big Data architectures, including distributed systems like Hadoop/Spark Includes accelerator-based approaches for big data applications such as GPU-based acceleration techniques, and hardware acceleration such as FPGA/CGRA/ASICs Presents emerging memory architectures and devices such as NVM, STT- RAM, 3D IC design principles Describes advanced algorithms for different big data application domains Illustrates novel analytics techniques for Big Data applications, scheduling, mapping, and partitioning methodologies Featuring contributions from leading experts, this book presents state-of-the-art research on the methodologies and applications of high-performance computing for big data applications. About the Editor Dr. Chao Wang is an Associate Professor in the School of Computer Science at the University of Science and Technology of China. He is the Associate Editor of ACM Transactions on Design Automations for Electronics Systems (TODAES), Applied Soft Computing, Microprocessors and Microsystems, IET Computers & Digital Techniques, and International Journal of Electronics. Dr. Chao Wang was the recipient of Youth Innovation Promotion Association, CAS, ACM China Rising Star Honorable Mention (2016), and best IP nomination of DATE 2015. He is now on the CCF Technical Committee on Computer Architecture, CCF Task Force on Formal Methods. He is a Senior Member of IEEE, Senior Member of CCF, and a Senior Member of ACM.
Big Data Data Mining And Machine Learning
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Author : Jared Dean
language : en
Publisher: John Wiley & Sons
Release Date : 2014-05-27
Big Data Data Mining And Machine Learning written by Jared Dean and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-27 with Computers categories.
With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.
High Performance Data Mining In Time Series
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Author : Yunyue Zhu
language : en
Publisher:
Release Date : 2004
High Performance Data Mining In Time Series written by Yunyue Zhu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.