Predictive Analytics Data Mining And Big Data


Predictive Analytics Data Mining And Big Data
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Predictive Analytics Data Mining And Big Data


Predictive Analytics Data Mining And Big Data
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Author : S. Finlay
language : en
Publisher: Springer
Release Date : 2014-07-01

Predictive Analytics Data Mining And Big Data written by S. Finlay and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-01 with Business & Economics categories.


This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.



Predictive Analytics


Predictive Analytics
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Author : Richard Hurley
language : en
Publisher:
Release Date : 2019-12-30

Predictive Analytics written by Richard Hurley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-30 with categories.


If you want to learn about predictive analytics without having to read a boring textbook, then keep reading... Companies are collecting more data from ever. With the ease of collecting all that data, all the different sources where you can receive the data, and the inexpensive storage, it makes sense to collect as much data as possible. But without a good analysis of that data, and without some time to really figure out what trends and insights are inside all of it, that data becomes worthless. 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. This guidebook is going to look at predictive analytics, and some of the topics we will explore concerning this topic include: The basics of predictive analysis. How to predict events that are going to happen in the future with big data and data mining. How to predict events that are going to happen in the future with the help of data analysis and statistics. A look at machine learning and how this process can help make predictions. How to avoid prediction traps, avoid bias, and make the best decisions with this analysis. Some of the top reasons to implement this kind of analysis in your business. The steps you can take to create your own predictive analysis model. And much, much more! Working on predictive analytics is going to be one of the best ways that your business can use the data you have to look more deeply inside, and sort through the different predictions you can make. Click the "add to cart" button to start your learning!



Big Data Analytics Methods


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.



Predictive Analytics For Dummies


Predictive Analytics For Dummies
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Author : Dr. Anasse Bari
language : en
Publisher: John Wiley & Sons
Release Date : 2016-09-16

Predictive Analytics For Dummies written by Dr. Anasse Bari 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 2016-09-16 with Business & Economics categories.


Use Big Data and technology to uncover real-world insights You don't need a time machine to predict the future. All it takes is a little knowledge and know-how, and Predictive Analytics For Dummies gets you there fast. With the help of this friendly guide, you'll discover the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data. In no time, you'll learn how to incorporate algorithms through data models, identify similarities and relationships in your data, and predict the future through data classification. Along the way, you'll develop a roadmap by preparing your data, creating goals, processing your data, and building a predictive model that will get you stakeholder buy-in. Big Data has taken the marketplace by storm, and companies are seeking qualified talent to quickly fill positions to analyze the massive amount of data that are being collected each day. If you want to get in on the action and either learn or deepen your understanding of how to use predictive analytics to find real relationships between what you know and what you want to know, everything you need is a page away! Offers common use cases to help you get started Covers details on modeling, k-means clustering, and more Includes information on structuring your data Provides tips on outlining business goals and approaches The future starts today with the help of Predictive Analytics For Dummies.



Predictive Analytics And Data Mining


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



Data Science


Data Science
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Author : Richard Hurley
language : en
Publisher:
Release Date : 2019-11-02

Data Science written by Richard Hurley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-02 with Big data categories.


If you want to learn about data science and big data, then keep reading... Two manuscripts in one book: Data Science: What You Need to Know About Data Analytics, Data Mining, Regression Analysis, Artificial Intelligence, Big Data for Business, Data Visualization, Database Querying, and Machine Learning Big Data: A Guide to Big Data Trends, Artificial Intelligence, Machine Learning, Predictive Analytics, Internet of Things, Data Science, Data Analytics, Business Intelligence, and Data Mining This book will discuss everything that you need to know when it comes to working in the field of data science. This world has changed, and with the modern technology that we have, it is easier than ever for companies to amass a large amount of data on the industry, on their competition, on their products, and their customers. Gathering the data is the easy part, though. Being able to sort through this data and understand what it is saying is going to be a unique challenge all on its own. This is where the process and field of data science can come in. There is so much that we can explore and learn about when it comes to the world of data science, and this ultimate guide is here to help you navigate through these specialties. You will see just how important the ideas of data mining, data analytics, and even artificial intelligence are to our world as a whole today. Some of the topics covered in part 1 of this book include: What is Data Science? What Exactly Does a Data Scientist Do? A Look at What Data Analytics Is All About What is Data Mining and How Does It Fit in with Data Science? Regression Analysis Why is Data Visualization So Important When It Comes to Understanding Your Data? How to work with Database Querying A Look at Artificial Intelligence What is Machine Learning and How Is It Different from Artificial Intelligence? What is the Future of Artificial Intelligence and Machine Learning? And much more! Some of the topics covered in part 2 of this book include: What is big data, and why is it important? The five V's behind big data How big data is already impacting your life, and where big data may be headed How big data and your everyday devices and appliances will come together in unexpected ways via the Internet of Things How companies and governments are using predictive analytics to get ahead of the competition or improve service How big data is used for fraud detection How big data can train intelligent computer systems The many ways large corporations are benefiting from big data and the tools that use it like machine learning, AI, and predictive analytics Upcoming trends in big data that are sure to have a large impact on your future Artificial intelligence, and how big data drives its development What machine learning is and how it is tied to big data The relationship between big data, data analytics, and business intelligence Insights into how big data impacts privacy issues The pros and cons regarding big data And much, much more! So if you want to learn more about data science and big data, click the "add to cart" button!



Big Data


Big Data
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Author : Richard Hurley
language : en
Publisher:
Release Date : 2019-09-28

Big Data written by Richard Hurley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-28 with categories.


If you want to learn about big data, then keep reading... Do you want to understand what big data is all about, but you don't get all the hype? Are you intrigued by the idea of building a career around big data and data science, but you just don't understand it? If so, this book could be what you are looking for. In this book, we will explore the hot concept of big data and explain it for beginners like yourself. If you know nothing about big data now, you will come away with a good overview of the subject and how it integrates into the other hot technologies of the day widely adopted by business, such as artificial intelligence, predictive analytics, and machine learning. Even if you don't intend to get directly involved in big data, understanding it will be very important in the coming years. It is one of the most important phenomena to hit in many years. It took some time for technology to catch up so that big data could be analyzed and processed, but now we are in the midst of a data revolution. Big data powers many of the world's most powerful companies, including Facebook, Amazon, and Google, among others. In this book, you will learn: What is big data, and why is it important? The five V's behind big data How big data is already impacting your life, and where big data may be headed How big data and your everyday devices and appliances will come together in unexpected ways via the Internet of Things How companies and governments are using predictive analytics to get ahead of the competition or improve service How big data is used for fraud detection How big data can train intelligent computer systems The many ways large corporations are benefiting from big data and the tools that use it like machine learning, AI, and predictive analytics Upcoming trends in big data that are sure to have a large impact on your future Artificial intelligence, and how big data drives its development What machine learning is and how it is tied to big data The relationship between big data, data analytics, and business intelligence Insights into how big data impacts privacy issues The pros and cons regarding big data And much, much more! If you want to learn about this new, exciting, and rapidly developing technology, then download this book right now! You will not be baffled by big data any longer, and you will understand the behavior of large companies far better than you ever did before.



Data Mining For Business Analytics


Data Mining For Business Analytics
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2016-04-22

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 2016-04-22 with Mathematics categories.


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 and more, the Third Edition also includes: Real-world examples to build a theoretical and practical understanding of key data mining methods End-of-chapter exercises that help readers better understand the presented material Data-rich case studies to illustrate various applications of data mining techniques Completely new chapters on social network analysis and text mining A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides https://www.dataminingbook.com Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. Praise for the Second Edition "…full of vivid and thought-provoking anecdotes... needs to be read by anyone with a serious interest in research and marketing."– Research Magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining - a welcome addition to the literature." – ComputingReviews.com "Excellent choice for business analysts...The book is a perfect fit for its intended audience." – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks and book chapters. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years.



Data Mining And Predictive Analytics


Data Mining And Predictive Analytics
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Author : Daniel T. Larose
language : en
Publisher: John Wiley & Sons
Release Date : 2015-02-19

Data Mining And Predictive Analytics written by Daniel T. Larose 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 2015-02-19 with Computers categories.


Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: 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 Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.



Data Analytics


Data Analytics
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Author : Arthur Zhang
language : en
Publisher:
Release Date : 2017-03-10

Data Analytics written by Arthur Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-10 with categories.


The Ultimate Guide to Data Science and Analytics This practical guide is accessible for the reader who is relatively new to the field of data analytics, while still remaining robust and detailed enough to function as a helpful guide to those already experienced in the field. Data science is expanding in breadth and growing rapidly in importance as technology rapidly integrates ever deeper into business and our daily lives. The need for a succinct and informal guide to this important field has never been greater. RIGHT NOW you can get ahead of the pack! This coherent guide covers everything you need to know on the subject of data science, with numerous concrete examples, and invites the reader to dive further into this exciting field. Students from a variety of academic backgrounds, including computer science, business, engineering, statistics, anyone interested in discovering new ideas and insights derived from data can use this as a textbook. At the same time, professionals such as managers, executives, professors, analysts, doctors, developers, computer scientists, accountants, and others can use this book to make a quantum leap in their knowledge of big data in a matter of only a few hours. Learn how to understand this field and uncover actionable insights from data through analytics. UNDERSTAND the following key insights when you grab your copy today: WHY DATA IS IMPORTANT TO YOUR BUSINESS DATA SOURCES HOW DATA CAN IMPROVE YOUR BUSINESS HOW BIG DATA CREATES VALUE DEVELOPMENT OF BIG DATA CONSIDERING THE PROS AND CONS OF BIG DATA BIG DATA FOR SMALL BUSINESSES THE COST EFFECTIVENESS OF DATA ANALYTICS WHAT TO CONSIDER WHEN PREPARING FOR A NEW BIG DATA SOLUTION DATA GATHERING DATA SCRUBBING DESCRIPTIVE ANALYTICS INFERENTIAL STATISTICS PREDICTIVE ANALYTICS PREDICTIVE MODELS DESCRIPTIVE MODELING DECISION MODELING PREDICTIVE ANALYSIS METHODS MACHINE LEARNING TECHNIQUES DATA ANALYSIS WITH "R" ANALYTICAL CUSTOMER RELATIONSHIP MANAGEMENT (CRM) THE USE OF PREDICTIVE ANALYTICS IN HEALTHCARE THE USE OF PREDICTIVE ANALYTICS IN THE FINANCIAL SECTOR PREDICTIVE ANALYTICS & BUSINESS MARKETING STRATEGIES FRAUD DETECTION SHIPPING BUSINESS CONTROLLING RISK FACTORS THE REVOLUTION OF PREDICTIVE ANALYSIS ACROSS A VARIETY OF INDUSTRIES DESCRIPTIVE AND PREDICTIVE ANALYSIS CRUCIAL FACTORS FOR DATA ANALYSIS RESOURCES AND FLEXIBLE TECHNICAL STRUCTURE BUSINESS INTELLIGENCE HYPER TARGETING WHAT IS DATA SCIENCE? DATA MUNGING DEMYSTIFYING DATA SCIENCE SECURITY RISKS TODAY BIG DATA AND IMPACTS ON EVERYDAY LIFE FINANCE AND BIG DATA APPLYING SENTIMENT ANALYSIS RISK EVALUATION AND THE DATA SCIENTIST THE FINANCE INDUSTRY AND REAL-TIME ANALYTICS HOW BIG DATA IS BENEFICIAL TO THE CUSTOMER CUSTOMER SEGMENTATION IS GOOD FOR BUSINESS USE OF BIG DATA BENEFITS IN MARKETING GOOGLE TRENDS THE PROFILE OF A PERFECT CUSTOMER LEAD SCORING IN PREDICTIVE ANALYSIS EVALUATING THE WORTH OF LIFETIME VALUE BIG DATA ADVANTAGES AND DISADVANTAGES MAKING COMPARISONS WITH COMPETITORS DATA SCIENCE IN THE TRAVEL SECTOR SAFETY ENHANCEMENTS THANKS TO BIG DATA BIG DATA AND AGRICULTURE BIG DATA AND LAW ENFORCEMENT THE USE OF BIG DATA IN THE PUBLIC SECTOR BIG DATA AND GAMING PRESCRIPTIVE ANALYTICS GOOGLE'S "SELF-DRIVING CAR" AND MUCH MORE! WANT MORE? Scroll up and grab this helpful guide toady!