Applying Predictive Analytics: Finding Value in Data, McCarthy Richard V., McCarthy Mary M., Ceccucci Wendy
Автор: Miller Thomas W. Jr. Название: Marketing Data Science: Modeling Techniques in Predictive Analytics with Python and R ISBN: 0133886557 ISBN-13(EAN): 9780133886559 Издательство: Pearson Education Рейтинг: Цена: 78530.00 T Наличие на складе: Поставка под заказ. Описание: Now, a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications.
Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes:
The role of analytics in delivering effective messages on the web
Understanding the web by understanding its hidden structures
Being recognized on the web - and watching your own competitors
Visualizing networks and understanding communities within them
Measuring sentiment and making recommendations
Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics
Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.
Автор: Larose Daniel T Название: Data Mining and Predictive Analytics ISBN: 1118116194 ISBN-13(EAN): 9781118116197 Издательство: Wiley Рейтинг: Цена: 125610.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 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.
Автор: Baesens Bart, Verbeke Wouter, Van Vlasselaer Veron Название: Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection ISBN: 1119133122 ISBN-13(EAN): 9781119133124 Издательство: Wiley Рейтинг: Цена: 41190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution.
Автор: Valentine Fontama; Roger Barga; Wee Hyong Tok Название: Predictive Analytics with Microsoft Azure Machine Learning 2nd Edition ISBN: 1484212010 ISBN-13(EAN): 9781484212011 Издательство: Springer Рейтинг: Цена: 41920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models.
Автор: Deep Название: Logistics, Supply Chain and Financial Predictive Analytics ISBN: 9811308713 ISBN-13(EAN): 9789811308710 Издательство: Springer Рейтинг: Цена: 167700.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: and determining initial, basic and feasible solutions for transportation problems by means of the "supply demand reparation method" and "continuous allocation method." In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices;
Автор: Michael Bowles Название: Machine Learning with Spark and Python: Essential Techniques for Predictive Analytics ISBN: 1119561930 ISBN-13(EAN): 9781119561934 Издательство: Wiley Рейтинг: Цена: 40120.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Cambridge for DGB 2nd Edition is a four-level American English integrated skills series for the Upper Secondary public school market in Mexico. Its syllabus is strictly aligned to the national Direccion General del Bachillerato program. It is a series that offers teachers a hands-on and practical solution to teaching English in the classroom. It builds students` language skills from A1 to A2+ in the CEFR.
Автор: Winters Ralph Название: Practical Predictive Analytics ISBN: 1785886185 ISBN-13(EAN): 9781785886188 Издательство: Неизвестно Рейтинг: Цена: 67430.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Kusum Deep; Madhu Jain; Said Salhi Название: Logistics, Supply Chain and Financial Predictive Analytics ISBN: 9811345228 ISBN-13(EAN): 9789811345227 Издательство: Springer Рейтинг: Цена: 167700.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book addresses a broad range of problems commonly encountered in the fields of financial analysis, logistics and supply chain management, such as the use of big data analytics in the banking sector. Divided into twenty chapters, some of the contemporary topics discussed in the book are co-operative/non-cooperative supply chain models for imperfect quality items with trade-credit financing; a non-dominated sorting water cycle algorithm for the cardinality constrained portfolio problem; and determining initial, basic and feasible solutions for transportation problems by means of the “supply demand reparation method” and “continuous allocation method.” In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices; optimal policy for Weibull distributed deteriorating items varying with ramp type demand rate and shortages; an inventory model with shortages and deterioration for three different demand rates; outlier labeling methods for medical data; a garbage disposal plant as a validated model of a fault-tolerant system; and the design of a “least cost ration formulation application for cattle”; a preservation technology model for deteriorating items with advertisement dependent demand and trade credit; a time series model for stock price forecasting in India; and asset pricing using capital market curves.The book offers a valuable asset for all researchers and industry practitioners working in these areas, giving them a feel for the latest developments and encouraging them to pursue further research in this direction.
Автор: Wu, James Coggeshall, Stephen Название: Foundations of predictive analytics ISBN: 0367381680 ISBN-13(EAN): 9780367381684 Издательство: Taylor&Francis Рейтинг: Цена: 63280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Drawing on the authors' two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It also discusses a variety of practical topics that are frequently missing from similar texts.
The book begins with the statistical and linear algebra/matrix foundation of modeling methods, from distributions to cumulant and copula functions to Cornish-Fisher expansion and other useful but hard-to-find statistical techniques. It then describes common and unusual linear methods as well as popular nonlinear modeling approaches, including additive models, trees, support vector machine, fuzzy systems, clustering, naпve Bayes, and neural nets. The authors go on to cover methodologies used in time series and forecasting, such as ARIMA, GARCH, and survival analysis. They also present a range of optimization techniques and explore several special topics, such as Dempster-Shafer theory.
An in-depth collection of the most important fundamental material on predictive analytics, this self-contained book provides the necessary information for understanding various techniques for exploratory data analysis and modeling. It explains the algorithmic details behind each technique (including underlying assumptions and mathematical formulations) and shows how to prepare and encode data, select variables, use model goodness measures, normalize odds, and perform reject inference.
Web Resource The book's website at www.DataMinerXL.com offers the DataMinerXL software for building predictive models. The site also includes more examples and information on modeling.
Автор: S. Finlay Название: Predictive Analytics, Data Mining and Big Data ISBN: 1349478687 ISBN-13(EAN): 9781349478682 Издательство: Springer Рейтинг: Цена: 32600.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 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.
Название: Computing Predictive Analytics, Business Intelligence, and Economics ISBN: 177188729X ISBN-13(EAN): 9781771887298 Издательство: Taylor&Francis Рейтинг: Цена: 118410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling.
Автор: Jones Herbert Название: Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database ISBN: 1647483263 ISBN-13(EAN): 9781647483265 Издательство: Неизвестно Рейтинг: Цена: 27580.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data science has a huge impact on how companies conduct business, and those who don`t learn about this revolutionaryfield could be left behind. You see, data science will help you make better decisions, know what products and services to release, and how to provide better service to your customers.
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