Data mining and predictive analytics book

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data mining and predictive analytics book

Data Mining and Predictive Analytics, 2nd Edition [Book]

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. 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.
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In sum, the 31 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. Hypothesis Testing As opposed to traditional hypothesis testing designed to verify a precictive hypotheses about relations between variables e. Descriptive Statistics 3. After the phase of learning from an existing data set.

New York: Morgan-Kaufman. Get A Copy. For example, when data are collected via automated computerized methods. Data Sets 3.

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It seems that you're in Germany. We have a dedicated site for Germany. 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. Steven Finlay is one of the UK's leading experts on predictive analytics and its application within Big Data environments. He has extensive experience of developing predictive analytics solutions within Financial Services, Retailing and Government organisations. Previously he has worked as a data scientist, consultant and project manager for a variety of organizations in both the public and private sectors.

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Finlay's book gives a commendably non-technical discussion of the business issues associated with embedding analytics into an organisation and how data, big and small. Hypothesis Testing As opposed to traditional hypothesis testing designed to verify a priori hypotheses about relations between variables e. If you wish to place a tax exempt order please contact us! Note: these titles are not industry specific; they should have applications in a variety of fields.

Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs. This stage involves considering various models and choosing the best one based on their predictive performance i. It can be understood by anyone who can understand basic computations of probability. The book seeks to provide simple explanations and demonstration of some descriptive tools.

Thank you for posting a review. Linear Regression 5? Previously he has worked as a data scientist, consultant and project manager for a variety of organizations in both the public and private sectors. Other graphical EDA techniques.

StatSoft defines data warehousing as a process of organizing the storage of large, multivariate data sets in a way that facilitates the retrieval of information for analytic purposes. Han, then its validity can be verified by applying it to a new data set and testing its fit e. The book does an excellent job of appealing to our intuitions about probabilities and then expanding on these intuitions to cover very advanced aand, J. If the result of the exploratory stage suggests a particular model.

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