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Machine Learning for Business Analytics
MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning —also known as data mining or data analytics— is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life ca...
Mobile Robot Navigation with Intelligent Infrared Image Interpretation
Mobile robots require the ability to make decisions such as "go through the hedges" or "go around the brick wall." Mobile Robot Navigation with Intelligent Infrared Image Interpretation describes in detail an alternative to GPS navigation: a physics-based adaptive Bayesian pattern classification model that uses a passive thermal infrared imaging system to automatically characterize non-heat generating objects in unstructured outdoor environments for mobile robots. The resulting classification model complements an autonomous robot’s situational awareness by providing the ability to classify smaller structures commonly found in the immediate operational environment.
Data Mining for Business Analytics
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...
Advances in Mathematical Finance
This self-contained volume brings together a collection of chapters by some of the most distinguished researchers and practitioners in the field of mathematical finance and financial engineering. Presenting state-of-the-art developments in theory and practice, the book has real-world applications to fixed income models, credit risk models, CDO pricing, tax rebates, tax arbitrage, and tax equilibrium. It is a valuable resource for graduate students, researchers, and practitioners in mathematical finance and financial engineering.
Operations Research, Computing, and Homeland Defense
This book is published in conjunction with the 12th Computing Society Conference, held January 9, 2011, in Monterey, California. The themes of the conference and this book are operations research, computing, and homeland defense. The papers cover topics on the theory of computing, mathematical programming, game theory, statistics and more; over half have applications to homeland defense.
Simulation-based Algorithms for Markov Decision Processes
Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences. This book brings the state-of-the-art research together for the first time. It provides practical modeling methods for many real-world problems with high dimensionality or complexity which have not hitherto been treatable with Markov decision processes.
Mathletics
"Mathletics shows readers how to use simple mathematics to analyze a range of statistical and probability-related questions in professional baseball, basketball, football, soccer, lacrosse, and golf, and in sports gambling. The authors describe the mathematical methods that top coaches and managers use to evaluate players and improve team performance, and give math enthusiasts the practical tools they need to enhance their understanding and enjoyment of their favorite sports - and maybe even gain the outside edge to winning bets. Mathletics blends fun and challenging math problems with sports stories of actual games, teams, and players, along with personal anecdotes from Winston's work as a ...
The Business of Pandemics
Nations and businesses across the globe have been working through the difficulties of dealing with the COVID-19 pandemic. Industry, academia, NGOs, and governments have been "feverishly" searching for ways to address this deadly virus, which may continue to spread for at least the next year and perhaps beyond (in terms of a resurgence and different strains). From a business standpoint, there have been dramatic effects on logistics and supply chains, economic downfalls, bailouts of major industries and small businesses, and far-reaching calamities from around the world. Even though the COVID-19 story is still in its making, this book focuses on the business of pandemics as applied to COVID-19...
CompTIA DataX Study Guide
Demonstrate your Data Science skills by earning the brand-new CompTIA DataX credential In CompTIA DataX Study Guide: Exam DY0-001, data scientist and analytics professor, Fred Nwanganga, delivers a practical, hands-on guide to establishing your credentials as a data science practitioner and succeeding on the CompTIA DataX certification exam. In this book, you'll explore all the domains covered by the new credential, which include key concepts in mathematics and statistics; techniques for modeling, analysis and evaluating outcomes; foundations of machine learning; data science operations and processes; and specialized applications of data science. This up-to-date Study Guide walks you through...
