Geo.Engineerings

Leonid Burstein ... 284 pages - Publisher: Woodhead Publishing; (February, 2020) ... Language: English - AmazonSIN: B084L22J54.

A MATLAB Primer for Technical Programming for Materials Science and Engineering draws on examples from the field, providing the latest information on this programming tool that is targeted towards materials science. The book enables non-programmers to master MATLAB in order to solve problems in materials science, assuming only a modest mathematical background. In addition, the book introduces programming and technical concepts in a logical manner to help students use MATLAB for subsequent projects. This title offers materials scientists who are non-programming specialists with a coherent and focused introduction to MATLAB. Provides the necessary background, alongside examples drawn from the field, to allow materials scientists to effectively master MATLAB. + Guides the reader through programming and technical concepts in a logical and coherent manner. + Promotes a thorough working familiarity with MATLAB for materials scientists. + Gives the information needed to write efficient and compact programs to solve problems in materials science, tribology, mechanics of materials and other material-related disciplines.

Gary Mavko, Tapan Mukerji, Jack Dvorkin ... 524 pages - Publisher: Cambridge University Press; 2nd edition (May, 2009) ... Language: English - ISBN-10: 0521861365.

This fully updated text addresses the relationships between geophysical observations and the underlying physical properties of rocks. It distills a vast quantity of background theory and laboratory results into a series of concise chapters that provide practical solutions to problems in geophysical data interpretation. Now in its second edition, major new chapters are presented on statistical rock physics and velocity-porosity-clay models for clastic sediments. Other new and expanded topics include anisotropic seismic signatures, borehole waves, models for fractured media, poroelastic models, and attenuation models. Also new to this edition is an enhanced set of appendices with key empirical results, data tables, and an atlas of reservoir rock properties - extended to include carbonates, clays, gas hydrates, and heavy oils. Supported by a website hosting MATLAB routines for implementing the various rock physics formulas, this book is a vital resource for advanced students and university faculty, as well as petroleum industry geophysicists and engineers.

Galit Shmueli, Peter C. Bruce, Nitin R. Patel ... 560 pages - Publisher: Wiley; 3rd edition (April, 2016) ... Language: English - ISBN-10: 1118729277 - ISBN-13: 978-1118729274.

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.

Iain Pardoe .. 346 pages - Publisher: Wiley; 2nd edition (July, 2012) ... Language: English - ISBN-10: 1118097289 - ISBN-13: 978-1118097281.

Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling.

In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction + Testing model assumptions + Nonconstant variance + Autocorrelation + Variable selection methods + Model building and graphical interpretation. Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos.

John D. Kelleher ... 296 pages - Publisher: The MIT Press (September, 2019) ... Language: English - ISBN-10: 0262537559 - ISBN-13: 978-0262537551.

An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.

470 pages - Publisher: Springer; (April, 2020) ... Language: English - AmazonSIN: B086S1JXRW.

This book explains the use of cloud computing systems for engineering applications to satisfy the need for enterprise level, state-of-the-art computational capacities at an affordable cost. As huge costs are involved in the maintenance and timely renovation of computational capabilities, particularly for projects that require significant computational capacity, cloud services can achieve considerable savings for users and organizations engaged in engineering research and development. Dr. Stradi-Granados explains how to extract a maximum value from every dollar invested in cloud computer server. The types of facilities located around the world that lease their resources to customers interested in reducing the internal overhead and implementation time. The volume features chapters on model generation, motion studies, and prototyping is ideal for students, researchers, practitioners, and facility's managers across a range of engineering domains.