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Author: Richard E. Neapolitan
Publisher: Elsevier
ISBN: 0080555675
Category : Mathematics
Languages : en
Pages : 427
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Book Description
Probabilistic Methods for Financial and Marketing Informatics aims to provide students with insights and a guide explaining how to apply probabilistic reasoning to business problems. Rather than dwelling on rigor, algorithms, and proofs of theorems, the authors concentrate on showing examples and using the software package Netica to represent and solve problems. The book contains unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance. It shares insights about when and why probabilistic methods can and cannot be used effectively. This book is recommended for all R&D professionals and students who are involved with industrial informatics, that is, applying the methodologies of computer science and engineering to business or industry information. This includes computer science and other professionals in the data management and data mining field whose interests are business and marketing information in general, and who want to apply AI and probabilistic methods to their problems in order to better predict how well a product or service will do in a particular market, for instance. Typical fields where this technology is used are in advertising, venture capital decision making, operational risk measurement in any industry, credit scoring, and investment science. Unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance Shares insights about when and why probabilistic methods can and cannot be used effectively Complete review of Bayesian networks and probabilistic methods for those IT professionals new to informatics.
Author: Richard E. Neapolitan
Publisher: Elsevier
ISBN: 0080555675
Category : Mathematics
Languages : en
Pages : 427
Get Book Here
Book Description
Probabilistic Methods for Financial and Marketing Informatics aims to provide students with insights and a guide explaining how to apply probabilistic reasoning to business problems. Rather than dwelling on rigor, algorithms, and proofs of theorems, the authors concentrate on showing examples and using the software package Netica to represent and solve problems. The book contains unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance. It shares insights about when and why probabilistic methods can and cannot be used effectively. This book is recommended for all R&D professionals and students who are involved with industrial informatics, that is, applying the methodologies of computer science and engineering to business or industry information. This includes computer science and other professionals in the data management and data mining field whose interests are business and marketing information in general, and who want to apply AI and probabilistic methods to their problems in order to better predict how well a product or service will do in a particular market, for instance. Typical fields where this technology is used are in advertising, venture capital decision making, operational risk measurement in any industry, credit scoring, and investment science. Unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance Shares insights about when and why probabilistic methods can and cannot be used effectively Complete review of Bayesian networks and probabilistic methods for those IT professionals new to informatics.
Author: Richard E. Neapolitan
Publisher: Morgan Kaufmann
ISBN: 0080919367
Category : Computers
Languages : en
Pages : 421
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Book Description
The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis. Unique coverage of probabilistic reasoning methods applied to bioinformatics data--those methods that are likely to become the standard analysis tools for bioinformatics. Shares insights about when and why probabilistic methods can and cannot be used effectively; Complete review of Bayesian networks and probabilistic methods with a practical approach.
Author: Richard E. Neapolitan
Publisher: CRC Press
ISBN: 1351384392
Category : Computers
Languages : en
Pages : 466
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Book Description
The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding. Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.
Author: Richard E. Neapolitan
Publisher: CRC Press
ISBN: 1466573198
Category : Computers
Languages : en
Pages : 508
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Book Description
The notion of artificial intelligence (AI) often sparks thoughts of characters from science fiction, such as the Terminator and HAL 9000. While these two artificial entities do not exist, the algorithms of AI have been able to address many real issues, from performing medical diagnoses to navigating difficult terrain to monitoring possible failures
Author: Richard Neapolitan
Publisher: Jones & Bartlett Learning
ISBN: 1284049191
Category : Computers
Languages : en
Pages : 694
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Book Description
Foundations of Algorithms, Fifth Edition offers a well-balanced presentation of algorithm design, complexity analysis of algorithms, and computational complexity. Ideal for any computer science students with a background in college algebra and discrete structures, the text presents mathematical concepts using standard English and simple notation to maximize accessibility and user-friendliness. Concrete examples, appendices reviewing essential mathematical concepts, and a student-focused approach reinforce theoretical explanations and promote learning and retention. C++ and Java pseudocode help students better understand complex algorithms. A chapter on numerical algorithms includes a review of basic number theory, Euclid's Algorithm for finding the greatest common divisor, a review of modular arithmetic, an algorithm for solving modular linear equations, an algorithm for computing modular powers, and the new polynomial-time algorithm for determining whether a number is prime. The revised and updated Fifth Edition features an all-new chapter on genetic algorithms and genetic programming, including approximate solutions to the traveling salesperson problem, an algorithm for an artificial ant that navigates along a trail of food, and an application to financial trading. With fully updated exercises and examples throughout and improved instructor resources including complete solutions, an Instructor's Manual and PowerPoint lecture outlines, Foundations of Algorithms is an essential text for undergraduate and graduate courses in the design and analysis of algorithms. Key features include: • The only text of its kind with a chapter on genetic algorithms • Use of C++ and Java pseudocode to help students better understand complex algorithms • No calculus background required • Numerous clear and student-friendly examples throughout the text • Fully updated exercises and examples throughout • Improved instructor resources, including complete solutions, an Instructor's Manual, and PowerPoint lecture outlines
Author: Gilles Barthe
Publisher: Cambridge University Press
ISBN: 110848851X
Category : Computers
Languages : en
Pages : 583
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Book Description
This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, security, and approximate computing. Comprehensive survey chapters make the material accessible to graduate students and non-experts. This title is also available as Open Access on Cambridge Core.
Author: Richard E. Neapolitan
Publisher: Jones & Bartlett Publishers
ISBN: 1284049205
Category : Algorithms
Languages : en
Pages : 694
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Book Description
Author: Soumen Chakrabarti
Publisher: Morgan Kaufmann
ISBN: 0080877885
Category : Computers
Languages : en
Pages : 477
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Book Description
This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics ? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology. The proposed book expertly combines the finest data mining material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining. This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources. Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints. Presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the reader’s technical expertise and ability to implement practical solutions. Coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases.
Author: Amal Ahmed
Publisher: Springer
ISBN: 3319898841
Category : Computers
Languages : en
Pages : 1056
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Book Description
This open access book constitutes the proceedings of the 27th European Symposium on Programming, ESOP 2018, which took place in Thessaloniki, Greece in April 2018, held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2018. The 36 papers presented in this volume were carefully reviewed and selected from 114 submissions. The papers are organized in topical sections named: language design; probabilistic programming; types and effects; concurrency; security; program verification; program analysis and automated verification; session types and concurrency; concurrency and distribution; and compiler verification.
Author: Daniel Adrian Doss
Publisher: CRC Press
ISBN: 1466592060
Category : Business & Economics
Languages : en
Pages : 756
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Book Description
From small law offices to federal agencies, all entities within the justice system are governed by complicated economic factors and face daily financial decision-making. A complement to Strategic Finance for Criminal Justice Organizations, this volume considers the justice system from a variety of economic and financial perspectives and introduces quantitative methods designed to improve the efficiency and effectiveness of organizations in both the non-profit and for-profit sectors. Using only a minimum of theory, Economic and Financial Analysis for Criminal Justice Organizations demonstrates how to make decisions in the justice system using multiple financial and economic models. Designed for readers with little knowledge of advanced mathematics, quantitative analysis, or spreadsheets, the book presents examples using straightforward, step-by-step processes with Excel and Linux Calc spreadsheet software. A variety of different types of decisions are considered, ranging from municipal bond issuance and valuation necessary for public revenues, pension planning, capital investment, determining the best use of monies toward construction projects, and other resource planning, allocation, and forecasting issues. From municipalities and police departments to for-profit prisons and security firms, the quantitative methods presented are designed to improve the efficiency and effectiveness of all organizations in the justice domain.
