RapidMiner

This book PDF is perfect for those who love Business & Economics genre, written by Markus Hofmann and published by CRC Press which was released on 19 April 2016 with total hardcover pages 525. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related RapidMiner books below.

RapidMiner
RapidMiner
Author : Markus Hofmann
File Size : 53,7 Mb
Publisher : CRC Press
Language : English
Release Date : 19 April 2016
ISBN : 9781482205503
Pages : 525 pages
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RapidMiner by Markus Hofmann Book PDF Summary

Powerful, Flexible Tools for a Data-Driven World As the data deluge continues in today’s world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making and forecasting, and ultimately the solution of increasingly complex problems. Learn from the Creators of the RapidMiner Software Written by leaders in the data mining community, including the developers of the RapidMiner software, RapidMiner: Data Mining Use Cases and Business Analytics Applications provides an in-depth introduction to the application of data mining and business analytics techniques and tools in scientific research, medicine, industry, commerce, and diverse other sectors. It presents the most powerful and flexible open source software solutions: RapidMiner and RapidAnalytics. The software and their extensions can be freely downloaded at www.RapidMiner.com. Understand Each Stage of the Data Mining Process The book and software tools cover all relevant steps of the data mining process, from data loading, transformation, integration, aggregation, and visualization to automated feature selection, automated parameter and process optimization, and integration with other tools, such as R packages or your IT infrastructure via web services. The book and software also extensively discuss the analysis of unstructured data, including text and image mining. Easily Implement Analytics Approaches Using RapidMiner and RapidAnalytics Each chapter describes an application, how to approach it with data mining methods, and how to implement it with RapidMiner and RapidAnalytics. These application-oriented chapters give you not only the necessary analytics to solve problems and tasks, but also reproducible, step-by-step descriptions of using RapidMiner and RapidAnalytics. The case studies serve as blueprints for your own data mining applications, enabling you to effectively solve similar problems.

RapidMiner

RapidMiner by Markus Hofmann,Ralf Klinkenberg

Powerful, Flexible Tools for a Data-Driven World As the data deluge continues in today’s world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making and forecasting, and ultimately the solution

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Principles and Theories of Data Mining With RapidMiner

Principles and Theories of Data Mining With RapidMiner by Ramjan, Sarawut,Sunkpho, Jirapon

The demand for skilled data scientists is rapidly increasing as more organizations recognize the value of data-driven decision- making. Data science, data management, and data mining are all critical components for various types of organizations, including large and small corporations, academic institutions, and government entities. For companies, these components serve

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Open Source Business Intelligence

Open Source Business Intelligence by Nils Clausen

This book presents an in-depth introduction to the characteristics and capabilities of two data-mining and business intelligence software packages: RapidMiner and the Jaspersoft Business Intelligence (BI) Suite.

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Data Mining

Data Mining by Richard J. Roiger

Data Mining: A Tutorial-Based Primer, Second Edition provides a comprehensive introduction to data mining with a focus on model building and testing, as well as on interpreting and validating results. The text guides students to understand how data mining can be employed to solve real problems and recognize whether a

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Data Science Business Analytics

Data Science Business Analytics by Sneha Kumari,K. K. Tripathy,Vidya Kumbhar

Data Science & Business Analytics explores the application of big data and business analytics by academics, researchers, industrial experts, policy makers and practitioners, helping the reader to understand how big data can be efficiently utilized in better managerial applications.

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Data Science Advancements in Pandemic and Outbreak Management

Data Science Advancements in Pandemic and Outbreak Management by Asimakopoulou, Eleana,Bessis, Nik

Pandemics are disruptive. Thus, there is a need to prepare and plan actions in advance for identifying, assessing, and responding to such events to manage uncertainty and support sustainable livelihood and wellbeing. A detailed assessment of a continuously evolving situation needs to take place, and several aspects must be brought

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Sports Data Mining

Sports Data Mining by Robert P. Schumaker,Osama K. Solieman,Hsinchun Chen

Data mining is the process of extracting hidden patterns from data, and it’s commonly used in business, bioinformatics, counter-terrorism, and, increasingly, in professional sports. First popularized in Michael Lewis’ best-selling Moneyball: The Art of Winning An Unfair Game, it is has become an intrinsic part of all professional sports

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Exploiting Semantic Web Knowledge Graphs in Data Mining

Exploiting Semantic Web Knowledge Graphs in Data Mining by P. Ristoski

Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the

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