Data Mining And Analytics
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Introduction To Data Mining And Analytics
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Author : Kris Jamsa
language : en
Publisher: Jones & Bartlett Learning
Release Date : 2020-02-03
Introduction To Data Mining And Analytics written by Kris Jamsa and has been published by Jones & Bartlett Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-03 with Computers categories.
Data Mining and Analytics provides a broad and interactive overview of a rapidly growing field. The exponentially increasing rate at which data is generated creates a corresponding need for professionals who can effectively handle its storage, analysis, and translation.
Exploring Advances In Interdisciplinary Data Mining And Analytics New Trends
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Author : Taniar, David
language : en
Publisher: IGI Global
Release Date : 2011-12-31
Exploring Advances In Interdisciplinary Data Mining And Analytics New Trends written by Taniar, David and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-31 with Computers categories.
"This book is an updated look at the state of technology in the field of data mining and analytics offering the latest technological, analytical, ethical, and commercial perspectives on topics in data mining"--Provided by publisher.
Data Mining For Business Analytics
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2019-10-14
Data Mining For Business Analytics written by Galit Shmueli 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 2019-10-14 with Mathematics categories.
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, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
Data Mining And Analytics
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Author : Alex Campbell
language : en
Publisher:
Release Date : 2020-09-28
Data Mining And Analytics written by Alex Campbell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-28 with categories.
Are you curious about data mining and analytics? Have you ever wondered how the world is filled with so much data and what is it used for? Do you wonder how companies use data to improve their revenue and steer themselves toward the path of success? Would you like to know why data is a new currency and companies invest so much to extract, store, and process data? Do you want to know how businesses leverage data to make millions of dollars in revenue? All of this can be achieved through data mining and analytics. If you are curious to know the answers to all these questions, this is the right book for you. This book will break down the terms data and mining for you so you can understand the concepts individually and then as a whole. If you have been looking to launch yourself into the world of data mining and data analytics, this book will serve as the perfect launchpad. The book will introduce you to all the concepts of data mining and analytics in a very tailored manner. It doesn't matter if you are a beginner in the field of data or a veteran; you will have something important to take away from this book. The tools and techniques described will teach you how data mining is used by organizations to steer themselves to success. This book will take you through: An overview of data mining and the need for data mining today Comparisons between data mining and data science The tasks and issues in data mining The terminologies used in data mining The data mining query language Classification, prediction, and cluster analysis in data mining This book has been tailored for you to understand data mining and analytics. There are step-by-step guides with code syntaxes so that you can understand various data mining techniques. If you're looking for the ultimate guide in mining, analytics and metrics, then grab your copy today!
Data Mining And Analysis
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Author : Mohammed J. Zaki
language : en
Publisher: Cambridge University Press
Release Date : 2014-05-12
Data Mining And Analysis written by Mohammed J. Zaki and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-12 with Computers categories.
A comprehensive overview of data mining from an algorithmic perspective, integrating related concepts from machine learning and statistics.
Social Media Data Mining And Analytics
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Author : Gábor Szabó
language : en
Publisher:
Release Date : 2019
Social Media Data Mining And Analytics written by Gábor Szabó and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with BUSINESS & ECONOMICS categories.
Multimedia Data Mining And Analytics
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Author : Aaron K. Baughman
language : en
Publisher: Springer
Release Date : 2015-03-31
Multimedia Data Mining And Analytics written by Aaron K. Baughman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-31 with Computers categories.
This book provides fresh insights into the cutting edge of multimedia data mining, reflecting how the research focus has shifted towards networked social communities, mobile devices and sensors. The work describes how the history of multimedia data processing can be viewed as a sequence of disruptive innovations. Across the chapters, the discussion covers the practical frameworks, libraries, and open source software that enable the development of ground-breaking research into practical applications. Features: reviews how innovations in mobile, social, cognitive, cloud and organic based computing impacts upon the development of multimedia data mining; provides practical details on implementing the technology for solving real-world problems; includes chapters devoted to privacy issues in multimedia social environments and large-scale biometric data processing; covers content and concept based multimedia search and advanced algorithms for multimedia data representation, processing and visualization.
Predictive Analytics And Data Mining
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Author : Vijay Kotu
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-11-27
Predictive Analytics And Data Mining written by Vijay Kotu and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-27 with Computers categories.
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
Big Data Analytics Methods
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Author : Peter Ghavami
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2019-12-16
Big Data Analytics Methods written by Peter Ghavami and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Business & Economics categories.
Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.
Data Analytics
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Author : Herbert Jones
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-09-19
Data Analytics written by Herbert Jones and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-19 with categories.
If you want to learn about data analytics and data mining then keep reading... 2 comprehensive manuscripts in 1 book Data Analytics: An Essential Beginner's Guide To Data Mining, Data Collection, Big Data Analytics For Business, And Business Intelligence Concepts Data Mining: The Data Mining Guide for Beginners, Including Applications for Business, Data Mining Techniques, Concepts, and More With this book, not only will you understand all the internal nitty-gritties about data analytics and data mining, you will also understand why data analytics and data mining is changing the business arena. You'll realize that the high-performance analytics will enable you to do stuff that you never thought about before probably because the volumes of data were just too big (among other reasons) and so much more. Here are just some of the topics that are discussed in the first part of this book: Overview Of Data Analytics: What Is Data Analytics (And Big Data Analytics)? Data Analytics And Business Intelligence Data Analysis And Data Analytics Data Mining Data Collection Types Of Data Analytics The Process: The Lifecycle Of Big Data Analytics Behavioral Analytics: Using Big Data Analytics To Find Hidden Customer Behavior Patterns Further Pattern Discovery In Advanced Analytics: Machine Learning And Much, Much More In part 2 of this book, you will learn the following: Model creation How to prepare your data How to clean your data Data Mining Similarity and distances of data The effect of data distribution Association pattern mining What is cluster analysis? What is an outlier in data mining? How to deal with outliers in data mining Methods of identifying outliers in data Applications of data mining in the business industry So if you are serious about becoming an expert in data analytics and data mining, start with this book by clicking "add to cart"!