Data Simplification

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  • Author : Jules J. Berman
  • Publisher : Morgan Kaufmann
  • Pages : 398 pages
  • ISBN : 0128038543
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Data Simplification

Download or Read online Data Simplification full in PDF, ePub and kindle. this book written by Jules J. Berman and published by Morgan Kaufmann which was released on 10 March 2016 with total page 398 pages. We cannot guarantee that Data Simplification book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification is the process whereby large and complex data is rendered usable. Complex data must be simplified before it can be analyzed, but the process of data simplification is anything but simple, requiring a specialized set of skills and tools. This book provides data scientists from every scientific discipline with the methods and tools to simplify their data for immediate analysis or long-term storage in a form that can be readily repurposed or integrated with other data. Drawing upon years of practical experience, and using numerous examples and use cases, Jules Berman discusses the principles, methods, and tools that must be studied and mastered to achieve data simplification, open source tools, free utilities and snippets of code that can be reused and repurposed to simplify data, natural language processing and machine translation as a tool to simplify data, and data summarization and visualization and the role they play in making data useful for the end user. Discusses data simplification principles, methods, and tools that must be studied and mastered Provides open source tools, free utilities, and snippets of code that can be reused and repurposed to simplify data Explains how to best utilize indexes to search, retrieve, and analyze textual data Shows the data scientist how to apply ontologies, classifications, classes, properties, and instances to data using tried and true methods

Data Simplification

Data Simplification
  • Author : Jules J. Berman
  • Publisher : Morgan Kaufmann
  • Release : 10 March 2016
GET THIS BOOK Data Simplification

Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification is the process whereby large and complex data is rendered usable. Complex data must be simplified before it can be analyzed, but the process of data simplification is anything but simple, requiring a specialized set of skills and tools. This book provides data scientists from every scientific discipline with the methods and

Data Simplification

Data Simplification
  • Author : Jules J. Berman
  • Publisher : Morgan Kaufmann Publishers
  • Release : 23 March 2016
GET THIS BOOK Data Simplification

Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification is the process whereby large and complex data is rendered usable. Complex data must be simplified before it can be analyzed, but the process of data simplification is anything but simple, requiring a specialized set of skills and tools. This book provides data scientists from every scientific discipline with the methods and

Appearance Preserving Data Simplification

Appearance Preserving Data Simplification
  • Author : Anonim
  • Publisher : Unknown
  • Release : 17 September 2021
GET THIS BOOK Appearance Preserving Data Simplification

Many visualization environments constantly face the issue of dealingwith large, complex datasets. Often these datasets are so complexthat rendering a visualization would seem impractical. Likewise, enormous amounts of data may overwhelm the human visual system; therebyrendering the data incomprehensible. Thus, the need arises to deal withthese datasets in some arbitrary manner such that the resultingdataset represents the original whole --- while reducing thecost on the human and computer visual system. A closely related problem can be found in geometric models,

Data Preprocessing in Data Mining

Data Preprocessing in Data Mining
  • Author : Salvador García,Julián Luengo,Francisco Herrera
  • Publisher : Springer
  • Release : 30 August 2014
GET THIS BOOK Data Preprocessing in Data Mining

Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the

Data Abstraction and Pattern Identification in Time series Data

Data Abstraction and  Pattern Identification  in Time series Data
  • Author : Prithiviraj Muthumanickam
  • Publisher : Linköping University Electronic Press
  • Release : 25 November 2019
GET THIS BOOK Data Abstraction and Pattern Identification in Time series Data

Data sources such as simulations, sensor networks across many application domains generate large volumes of time-series data which exhibit characteristics that evolve over time. Visual data analysis methods can help us in exploring and understanding the underlying patterns present in time-series data but, due to their ever-increasing size, the visual data analysis process can become complex. Large data sets can be handled using data abstraction techniques by transforming the raw data into a simpler format while, at the same time,

Digital Imaging for Cultural Heritage Preservation

Digital Imaging for Cultural Heritage Preservation
  • Author : Filippo Stanco,Sebastiano Battiato,Giovanni Gallo
  • Publisher : CRC Press
  • Release : 28 July 2011
GET THIS BOOK Digital Imaging for Cultural Heritage Preservation

This edition presents the most prominent topics and applications of digital image processing, analysis, and computer graphics in the field of cultural heritage preservation. The text assumes prior knowledge of digital image processing and computer graphics fundamentals. Each chapter contains a table of contents, illustrations, and figures that elucidate the presented concepts in detail, as well as a chapter summary and a bibliography for further reading. Well-known experts cover a wide range of topics and related applications, including spectral imaging,

Analysis of Neural Data

Analysis of Neural Data
  • Author : Robert E. Kass,Uri T. Eden,Emery N. Brown
  • Publisher : Springer
  • Release : 08 July 2014
GET THIS BOOK Analysis of Neural Data

Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among

Analytics and Big Data for Accountants

Analytics and Big Data for Accountants
  • Author : Jim Lindell
  • Publisher : John Wiley & Sons
  • Release : 23 March 2018
GET THIS BOOK Analytics and Big Data for Accountants

Analytics is the new force driving business. Tools have been created to measure program impacts and ROI, visualize data and business processes, and uncover the relationship between key performance indicators, many using the unprecedented amount of data now flowing into organizations. Featuring updated examples and surveys, this dynamic book covers leading-edge topics in analytics and finance. It is packed with useful tips and practical guidance you can apply immediately. This book prepares accountants to: Deal with major trends in predictive

Logic and Critical Thinking in the Biomedical Sciences

Logic and Critical Thinking in the Biomedical Sciences
  • Author : Jules J. Berman
  • Publisher : Academic Press
  • Release : 08 July 2020
GET THIS BOOK Logic and Critical Thinking in the Biomedical Sciences

All too often, individuals engaged in the biomedical sciences assume that numeric data must be left to the proper authorities (e.g., statisticians and data analysts) who are trained to apply sophisticated mathematical algorithms to sets of data. This is a terrible mistake. Individuals with keen observational skills, regardless of their mathematical training, are in the best position to draw correct inferences from their own data and to guide the subsequent implementation of robust, mathematical analyses. Volume 2 of Logic and

Geometric Modeling for Scientific Visualization

Geometric Modeling for Scientific Visualization
  • Author : Guido Brunnett,Bernd Hamann,Heinrich Müller,Lars Linsen
  • Publisher : Springer Science & Business Media
  • Release : 17 April 2013
GET THIS BOOK Geometric Modeling for Scientific Visualization

Geometric Modeling and Scientific Visualization are both established disciplines, each with their own series of workshops, conferences and journals. But clearly both disciplines overlap; this observation led to the idea of composing a book on Geometric Modeling for Scientific Visualization.

Data Democracy

Data Democracy
  • Author : Feras A. Batarseh,Ruixin Yang
  • Publisher : Academic Press
  • Release : 21 January 2020
GET THIS BOOK Data Democracy

Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering provides a manifesto to data democracy. After reading the chapters of this book, you are informed and suitably warned! You are already part of the data republic, and you (and all of us) need to ensure that our data fall in the right hands. Everything you click, buy, swipe, try, sell, drive, or fly is a data point. But who owns the data? At this point, not

Heterogeneous Spatial Data

Heterogeneous Spatial Data
  • Author : Giuseppe Patanè,Michela Spagnuolo
  • Publisher : Morgan & Claypool Publishers
  • Release : 29 April 2016
GET THIS BOOK Heterogeneous Spatial Data

New data acquisition techniques are emerging and are providing fast and efficient means for multidimensional spatial data collection. Airborne LIDAR surveys, SAR satellites, stereo-photogrammetry and mobile mapping systems are increasingly used for the digital reconstruction of the environment. All these systems provide extremely high volumes of raw data, often enriched with other sensor data (e.g., beam intensity). Improving methods to process and visually analyze this massive amount of geospatial and user-generated data is crucial to increase the efficiency of

Statistical Data Cleaning with Applications in R

Statistical Data Cleaning with Applications in R
  • Author : Mark van der Loo,Edwin de Jonge
  • Publisher : John Wiley & Sons
  • Release : 29 January 2018
GET THIS BOOK Statistical Data Cleaning with Applications in R

A comprehensive guide to automated statistical data cleaning The production of clean data is a complex and time-consuming process that requires both technical know-how and statistical expertise. Statistical Data Cleaning brings together a wide range of techniques for cleaning textual, numeric or categorical data. This book examines technical data cleaning methods relating to data representation and data structure. A prominent role is given to statistical data validation, data cleaning based on predefined restrictions, and data cleaning strategy. Key features: Focuses