Predictive Analytics and Data Mining

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  • Author : Vijay Kotu
  • Publisher : Morgan Kaufmann
  • Pages : 446 pages
  • ISBN : 0128016507
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Predictive Analytics and Data Mining

Download or Read online Predictive Analytics and Data Mining full in PDF, ePub and kindle. this book written by Vijay Kotu and published by Morgan Kaufmann which was released on 27 November 2014 with total page 446 pages. We cannot guarantee that Predictive Analytics and Data Mining 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. Put Predictive Analytics into Action Learn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining. You’ll be able to: 1. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general purpose analytics process. 2. Get up and running fast with more than two dozen commonly used powerful algorithms for predictive analytics using practical use cases. 3. Implement a simple step-by-step process for predicting an outcome or discovering hidden relationships from the data using RapidMiner, an open source GUI based data mining tool Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest Neighbors, Naïve Bayesian, Artificial Neural Networks, Support Vector machines, Ensemble models, Bagging, Boosting, Random Forests, Linear regression, Logistic regression, Association analysis using Apriori and FP Growth, K-Means clustering, Density based clustering, Self Organizing Maps, Text Mining, Time series forecasting, Anomaly detection and Feature selection. Implementation files can be downloaded from the book companion site at www.LearnPredictiveAnalytics.com Demystifies data mining concepts with easy to understand language Shows how to get up and running fast with 20 commonly used powerful techniques for predictive analysis Explains the process of using open source RapidMiner tools Discusses a simple 5 step process for implementing algorithms that can be used for performing predictive analytics Includes practical use cases and examples

Predictive Analytics and Data Mining

Predictive Analytics and Data Mining
  • Author : Vijay Kotu,Bala Deshpande
  • Publisher : Morgan Kaufmann
  • Release : 27 November 2014
GET THIS BOOK Predictive Analytics and Data Mining

Put Predictive Analytics into Action Learn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores

Data Mining and Predictive Analytics

Data Mining and Predictive Analytics
  • Author : Daniel T. Larose,Chantal D. Larose
  • Publisher : John Wiley & Sons
  • Release : 16 March 2015
GET THIS BOOK Data Mining and Predictive Analytics

Learn methods of data analysis and their application to real-world data sets. Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content

Data Mining and Predictive Analysis

Data Mining and Predictive Analysis
  • Author : Colleen McCue
  • Publisher : Butterworth-Heinemann
  • Release : 02 January 2015
GET THIS BOOK Data Mining and Predictive Analysis

Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive, security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining in homeland security, security analysis,

Predictive Data Mining Models

Predictive Data Mining Models
  • Author : David L. Olson,Desheng Wu
  • Publisher : Springer
  • Release : 07 August 2019
GET THIS BOOK Predictive Data Mining Models

This book provides an overview of predictive methods demonstrated by open source software modeling with Rattle (R’) and WEKA. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also

Descriptive Data Mining

Descriptive Data Mining
  • Author : David L. Olson,Georg Lauhoff
  • Publisher : Springer
  • Release : 06 May 2019
GET THIS BOOK Descriptive Data Mining

This book provides an overview of data mining methods demonstrated by software. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Diagnostic analytics can apply

Commercial Data Mining

Commercial Data Mining
  • Author : David Nettleton
  • Publisher : Morgan Kaufmann
  • Release : 21 June 2021
GET THIS BOOK Commercial Data Mining

Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business

Data Mining for Business Analytics

Data Mining for Business Analytics
  • Author : Galit Shmueli,Peter C. Bruce,Nitin R. Patel
  • Publisher : John Wiley & Sons
  • Release : 22 April 2016
GET THIS BOOK Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling

Predictive Analytics

Predictive Analytics
  • Author : Richard Hurley
  • Publisher : Unknown
  • Release : 19 January 2020
GET THIS BOOK Predictive Analytics

This is where predictive analytics is going to come in handy. You will be able to actually take all of the data that you have been collecting and storing, and see what insights are in there to lead some of your business decisions in the future.

Predictive Analytics for Marketers

Predictive Analytics for Marketers
  • Author : Barry Leventhal
  • Publisher : Kogan Page Publishers
  • Release : 03 February 2018
GET THIS BOOK Predictive Analytics for Marketers

Predictive analytics has revolutionized marketing practice. It involves using many techniques from data mining, statistics, modelling, machine learning and artificial intelligence, to analyse current data and make predictions about unknown future events. In business terms, this enables companies to forecast consumer behaviour and much more. Predictive Analytics for Marketers will guide marketing professionals on how to apply predictive analytical tools to streamline business practices. Including comprehensive coverage of an array of predictive analytic tools and techniques, this book enables readers

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications
  • Author : Robert Nisbet,Gary Miner,Ken Yale
  • Publisher : Elsevier
  • Release : 09 November 2017
GET THIS BOOK Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and

Data Mining and Predictive Analysis

Data Mining and Predictive Analysis
  • Author : Colleen McCue
  • Publisher : Elsevier
  • Release : 17 October 2006
GET THIS BOOK Data Mining and Predictive Analysis

It is now possible to predict the future when it comes to crime. In Data Mining and Predictive Analysis, Dr. Colleen McCue describes not only the possibilities for data mining to assist law enforcement professionals, but also provides real-world examples showing how data mining has identified crime trends, anticipated community hot-spots, and refined resource deployment decisions. In this book Dr. McCue describes her use of "off the shelf" software to graphically depict crime trends and to predict where future crimes

Applied Predictive Analytics

Applied Predictive Analytics
  • Author : Dean Abbott
  • Publisher : John Wiley & Sons
  • Release : 31 March 2014
GET THIS BOOK Applied Predictive Analytics

Learn the art and science of predictive analytics — techniques that get results Predictive analytics is what translates big data into meaningful, usable business information. Written by a leading expert in the field, this guide examines the science of the underlying algorithms as well as the principles and best practices that govern the art of predictive analytics. It clearly explains the theory behind predictive analytics, teaches the methods, principles, and techniques for conducting predictive analytics projects, and offers tips and tricks

Data Mining for Business Analytics

Data Mining for Business Analytics
  • Author : Galit Shmueli,Peter C. Bruce,Peter Gedeck,Nitin R. Patel
  • Publisher : John Wiley & Sons
  • Release : 05 November 2019
GET THIS BOOK Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction,