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data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data;
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R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for;
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Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining;
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Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining;
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and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and;
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are a budding data scientist, or a data analyst with a basic knowledge of R, and want to get into the intricacies of data mining in a;
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Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and;
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an R programmer, analyst, or data scientist who wants to gain experience in performing text data mining and analytics with R, then this book;
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Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro(R) presents an applied and interactive approach to;
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data using magrittr and dplyr Write functions with R for data science, data mining, and analytics-based applications Visualize data with;
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then transform that data using magrittr and dplyr Write functions with R for data science, data mining, and analytics-based applications;
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Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a do-it-yourself approach;
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Write functions with R for data science, data mining, and analytics-based applications Visualize data with ggplot2 and fit data to models using;
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With its state-of-the-art capabilities for rapidly processing and retrieving huge quantities of data, Microsoft(R) SQL Server 2000;
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with widely available free software. The book focuses on demonstrating common business data mining applications. It provides exposure to the;
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introduction to statistical methods for data mining and knowledge discovery. Extensive solutions using actual data (with sample R programming code) are;
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demonstrating the internal operation and usage of data mining algorithms using examples in R.;
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data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics;
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analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big;
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business solutions-practical, up-to-date, and hands-on! With data mining, you can achieve competitive advantage from the data you've already paid;
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that can provide marketers with detailed information about the products, content, and services their customers desire. Data Mining Mobile;
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that can provide marketers with detailed information about the products, content, and services their customers desire. Data Mining Mobile;
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mining implementation using R and Rattle open source data mining tools. . Technical topics discussed in the book include: * Emerging Research;
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Gain sharp insights into your data and solve real-world data science problems with R-from data munging to modeling and visualization;
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Get to grips with key data visualization and predictive analytic skills using R About This Book * Acquire predictive analytic skills;
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scientists and data scientists that know R and would like to learn Python or are familiar with Python and want to learn R. It also functions as;
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Use R for efficient data mining, text analytics and feature engineering Become a thorough data science professional with the help of hands-on;
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