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Introduction to Data Mining and Analytics

Introduction to Data Mining and Analytics PDF Author: Kris Jamsa
Publisher: Jones & Bartlett Learning
ISBN: 1284180905
Category : Computers
Languages : en
Pages : 668

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Book Description
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.

Introduction to Data Mining and Analytics

Introduction to Data Mining and Analytics PDF Author: Kris Jamsa
Publisher: Jones & Bartlett Learning
ISBN: 1284180905
Category : Computers
Languages : en
Pages : 668

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Book Description
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.

Discovering Knowledge in Data

Discovering Knowledge in Data PDF Author: Daniel T. Larose
Publisher: John Wiley & Sons
ISBN: 0470908742
Category : Computers
Languages : en
Pages : 336

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Book Description
The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before. This book provides the tools needed to thrive in today’s big data world. The author demonstrates how to leverage a company’s existing databases to increase profits and market share, and carefully explains the most current data science methods and techniques. The reader will “learn data mining by doing data mining”. By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, Discovering Knowledge in Data, Second Edition remains the eminent reference on data mining. The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis. Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and Visualization Offers extensive coverage of the R statistical programming language Contains 280 end-of-chapter exercises Includes a companion website for university instructors who adopt the book

Introduction to Data Mining and Its Applications

Introduction to Data Mining and Its Applications PDF Author: S. Sumathi
Publisher: Springer Science & Business Media
ISBN: 3540343504
Category : Computers
Languages : en
Pages : 828

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Book Description
This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.

A General Introduction to Data Analytics

A General Introduction to Data Analytics PDF Author: João Moreira
Publisher: John Wiley & Sons
ISBN: 1119296242
Category : Mathematics
Languages : en
Pages : 352

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Book Description
A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniques A unique illustrative example that extends throughout all the chapters Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.

Data Mining for the Social Sciences

Data Mining for the Social Sciences PDF Author: Paul Attewell
Publisher: Univ of California Press
ISBN: 0520280989
Category : Political Science
Languages : en
Pages : 252

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Book Description
"We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher.

Data Mining and Predictive Analytics

Data Mining and Predictive Analytics PDF Author: Daniel T. Larose
Publisher: John Wiley & Sons
ISBN: 1118116194
Category : Computers
Languages : en
Pages : 824

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Book Description
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 Analytics For Beginners

Data Analytics For Beginners PDF Author: Anthony S. Williams
Publisher: Anthony S. Williams
ISBN:
Category : Computers
Languages : en
Pages : 109

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Book Description
Data Analytics For Beginners Knowing the data generated by your business every day is a key to success in the Data Analytic World that you are competing in. As there is so much data so, the organizations need to collect and store them. The data becomes valuable to businesses when it is analyzed. Prior to the recent rise in analytics, businesses and organizations did not have the capacity to analyze a great deal of data, so a relatively small amount was maintained. In today's data-driven world, anything and everything may have significance, so there has been an attempt to record and keep virtually any data that we have the capacity to collect; and we have a great deal of capacity. There is so much to learn in this book about data analytics and I do invite you to grab your copy today and get started! By downloading this book you will discover... Putting Data Analytics to Work The Rise of Data Analytics Big Data Defined Cluster Analysis Applications of Cluster Analysis Commonly Graphed Information Data Visualization Four Important Features of Data Visualization Software Big Data Impact Envisaged by 2020 Pros and Cons of Big Data Analytics And of course much more! Get this book today and learn more about Data Analytics!

Data Mining: the Money Is in the Data

Data Mining: the Money Is in the Data PDF Author: O. Theobald
Publisher:
ISBN: 9781520867588
Category :
Languages : en
Pages : 88

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Book Description
I'm going to start with a hypothesis. This hypothesis predicts that you've already read about big data. Perhaps because you read regularly about technology on Tech Crunch or Fast Company, or maybe you've bought a book about big data on Amazon. But after reading 15 case studies on how big data is transforming business you start to get impatient. You want to unlock the massive power of big data, start your own small projects and add 'Data Mining' as a skill to your LinkedIn profile. The term 'data mining' even sounds cool. It has a similar ring to 'Bit Coin Mining,' and evokes the notion of prospecting for wealth. "Oh hey John how was your weekend?" Your colleague asks you on Monday morning. "Nothing special. Took this weekend pretty easy, bought a couple new video games. Oh and that's right... (feigning like this is not what you've been waiting to share all along) and Sunday afternoon I crushed out some data mining reports on Hadoop at this awesome new coffee shop down the road. I think this will double our expected sales revenue for the spring quarter." To act modest, you add on a quick remark about trying de-constructed coffee for the first time. Data Mining is definitely not as sexy as this fictional story makes out. Dating mining skills take significant dedication and time to develop, and is not something you can learn in a weekend. But it is true that data mining is intertwined with very high earning potential (six figures), and business growth. This book is written for beginners to data science who are interested in making sense of large volumes of data to uncover new insight, assist decision-making and gain a competitive edge. If you are currently a student or already working in marketing, medical research, senior management, policy analysis or IT then this book is ideally suited for you. What you learn from reading this book - Data Mining Infrastructure- Data Mining Software- Web Scraping (without code)- Downloading Free Datasets- Data Mining Techniques: Regression, Clustering, Anomaly Detection, Text Mining, Association Analysis & More.- Data Mining Visualization- Data Mining Careers- Machine Learning- Big Data Analytics Click buy above to dive into Data Mining!

Statistical Data Analytics

Statistical Data Analytics PDF Author: Walter W. Piegorsch
Publisher: John Wiley & Sons
ISBN: 111861965X
Category : Mathematics
Languages : en
Pages : 464

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Book Description
Statistical Data Analytics Statistical Data Analytics Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery Applications of data mining and ‘big data’ increasingly take center stage in our modern, knowledge-driven society, supported by advances in computing power, automated data acquisition, social media development and interactive, linkable internet software. This book presents a coherent, technical introduction to modern statistical learning and analytics, starting from the core foundations of statistics and probability. It includes an overview of probability and statistical distributions, basics of data manipulation and visualization, and the central components of standard statistical inferences. The majority of the text extends beyond these introductory topics, however, to supervised learning in linear regression, generalized linear models, and classification analytics. Finally, unsupervised learning via dimension reduction, cluster analysis, and market basket analysis are introduced. Extensive examples using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others. Statistical Data Analytics: Focuses on methods critically used in data mining and statistical informatics. Coherently describes the methods at an introductory level, with extensions to selected intermediate and advanced techniques. Provides informative, technical details for the highlighted methods. Employs the open-source R language as the computational vehicle – along with its burgeoning collection of online packages – to illustrate many of the analyses contained in the book. Concludes each chapter with a range of interesting and challenging homework exercises using actual data from a variety of informatic application areas. This book will appeal as a classroom or training text to intermediate and advanced undergraduates, and to beginning graduate students, with sufficient background in calculus and matrix algebra. It will also serve as a source-book on the foundations of statistical informatics and data analytics to practitioners who regularly apply statistical learning to their modern data.

Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends

Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends PDF Author: Taniar, David
Publisher: IGI Global
ISBN: 1613504756
Category : Computers
Languages : en
Pages : 465

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Book Description
"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.