37,30 zł

Dynamic Programming for the day before your coding interview Independently Published

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Dynamic Programming is a fundamental algorithmic technique which is behind solving some of the toughest computing problems. In this book, we have covered some Dynamic Programming problems which will give you the general idea of formulating a Dynamic Programming solution and practice on applying it on a variety of problems with focus on Coding Interview.Some of the problems we have covered are:Permutation coefficient: This is a basic problem but is significant in understanding the idea behind Dynamic Programming.Longest Common Substring: This is an important problem as we see how we can apply Dynamic Programming in string problems.XOR value: This is another significant problem as we are applying Dynamic Programming on a Number Theory problem more specifically problem involving subset generation.K edges: In line with our previous problems, in this problem, we have applied Dynamic Programming in a graph-based problem. This problem shows a problem where Dynamic Programming is not the most efficient solution but is in the right path.We have covered other relevant solutions and ideas so that you have the complete idea of the problems and understand deeply the significance of Dynamic Programming in respect to the problems.Book: Dynamic Programming for the day before your Coding InterviewAuthors (2): Aditya Chatterjee, Ue KiaoAbout the authors:Aditya Chatterjee is an Independent Researcher, Technical Author and the Founding Member of OPENGENUS, a scientific community focused on Computing Technology.Ue Kiao is a Japanese Software Developer and has played key role in designing systems like TaoBao, AliPay and many more. She has completed her B. Sc in Mathematics and Computing Science at National Taiwan University and PhD at Tokyo Institute of Technology.

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279,97 zł

Dynamic Programming of Economic Decisions Springer-Verlag Berlin and Heidelberg GmbH & Co....

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Dynamic Programming is the analysis of multistage decision in the sequential mode. It is now widely recognized as a tool of great versatility and power, and is applied to an increasing extent in all phases of economic analysis, operations research, technology, and also in mathematical theory itself. In economics and operations research its impact may someday rival that of linear programming. The importance of this field is made apparent through a growing number of publications. Foremost among these is the pioneering work of Bellman. It was he who originated the basic ideas, formulated the principle of optimality, recognized its power, coined the terminology, and developed many of the present applications. Since then mathe maticians, statisticians, operations researchers, and economists have come in, laying more rigorous foundations [KARLIN, BLACKWELL], and developing in depth such application as to the control of stochastic processes [HoWARD, JEWELL]. The field of inventory control has almost split off as an independent branch of Dynamic Programming on which a great deal of effort has been expended [ARRoW, KARLIN, SCARF], [WIDTIN] , [WAGNER]. Dynamic Programming is also playing an in creasing role in modem mathematical control theory [BELLMAN, Adap tive Control Processes (1961)]. Some of the most exciting work is going on in adaptive programming which is closely related to sequential statistical analysis, particularly in its Bayesian form. In this monograph the reader is introduced to the basic ideas of Dynamic Programming.

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209,99 zł

Dynamic Programming

Książki Obcojęzyczne>Angielskie>Computing & information technology>Computer science>Systems analysis & designKsiążki Obcojęzyczne>Angie...

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Sklep: Gigant.pl

549,39 zł

Methods for Applied Macroeconomic Research Princeton University Press

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The last twenty years have witnessed tremendous advances in the mathematical, statistical, and computational tools available to applied macroeconomists. This rapidly evolving field has redefined how researchers test models and validate theories. Yet until now there has been no textbook that unites the latest methods and bridges the divide between theoretical and applied work. Fabio Canova brings together dynamic equilibrium theory, data analysis, and advanced econometric and computational methods to provide the first comprehensive set of techniques for use by academic economists as well as professional macroeconomists in banking and finance, industry, and government. This graduate-level textbook is for readers knowledgeable in modern macroeconomic theory, econometrics, and computational programming using RATS, MATLAB, or Gauss. Inevitably a modern treatment of such a complex topic requires a quantitative perspective, a solid dynamic theory background, and the development of empirical and numerical methods - which is where Canova's book differs from typical graduate textbooks in macroeconomics and econometrics.Rather than list a series of estimators and their properties, Canova starts from a class of DSGE models, finds an approximate linear representation for the decision rules, and describes methods needed to estimate their parameters, examining their fit to the data. The book is complete with numerous examples and exercises. Today's economic analysts need a strong foundation in both theory and application. "Methods for Applied Macroeconomic Research" offers the essential tools for the next generation of macroeconomists.

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279,97 zł

Introduction to Optimization Springer-Verlag New York Inc.

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This undergraduate textbook introduces students of science and engineering to the fascinating field of optimization. It is a unique book that brings together the subfields of mathematical programming, variational calculus, and optimal control, thus giving students an overall view of all aspects of optimization in a single reference. As a primer on optimization, its main goal is to provide a succinct and accessible introduction to linear programming, nonlinear programming, numerical optimization algorithms, variational problems, dynamic programming, and optimal control. Prerequisites have been kept to a minimum, although a basic knowledge of calculus, linear algebra, and differential equations is assumed.§This undergraduate textbook introduces students of science and engineering to the fascinating field of optimization. It is a unique book that brings together the subfields of mathematical programming, variational calculus, and optimization in a single reference. As a primer on optimization, its main goal is to provide a succinct and accessible introduction to linear programming, nonlinear programming, numerical optimization algorithms, variational problems, dynamic programming, and optimal control. Prerequisites have been kept to a minimum, although a basic knowledge of calculus, linear algebra, and differential equations is assumed.§There are numerous examples, illustrations, and exercises throughout the text, making it an ideal book for self-study. Applied mathematicians, physicists, engineers, and scientists will find this introduction to optimization extremely useful.

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667,52 zł

Simulation-Based Optimization Springer-Verlag New York Inc.

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Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques - especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms.Key features of this revised and improved Second Edition include:

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260,13 zł

Designing Human-Centric AI Experiences APress

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User experience (UX) design practices have seen a fundamental shift as more and more software products incorporate machine learning (ML) components and artificial intelligence (AI) algorithms at their core. This book will probe into UX design's role in making technologies inclusive and enabling user collaboration with AI.AI/ML-based systems have changed the way of traditional UX design. Instead of programming a method to do a specific action, creators of these systems provide data and nurture them to curate outcomes based on inputs. These systems are dynamic and while AI systems change over time, their user experience, in many cases, does not adapt to this dynamic nature. Applied UX Design for Artificial Intelligence will explore this problem, addressing the challenges and opportunities in UX design for AI/ML systems, look at best practices for designers, managers, and product creators and showcase how individuals from a non-technical background can collaborate effectively with AI and Machine learning teams.What You'll Learn:Best practices in UX design when building human-centric AI products or featuresAbility to spot opportunities for applying AI in their organizationsAdvantages and limitations of AI when building software productsAbility to collaborate and communicate effectively with AI/ML tech teamsUX design for different modalities (voice, speech, text, etc.)Designing ethical AI systemsWho This Book Is For:The primary audience is UX Designers, researchers, managers, and technologists working with or interested in building human-centered AI/ML products. Little to no technical expertise in the technology is required. Additionally, theis book can help startup founders identify opportunities and build desirable AI products. It could also be relevant for developers interested in building intuitive interfaces for AI-based solutions.

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383,10 zł

Design of Approximation Algorithms Cambridge University Press

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Discrete optimization problems are everywhere, from traditional operations research planning (scheduling, facility location and network design); to computer science databases; to advertising issues in viral marketing. Yet most such problems are NP-hard; unless P = NP, there are no efficient algorithms to find optimal solutions. This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. The book is organized around central algorithmic techniques for designing approximation algorithms, including greedy and local search algorithms, dynamic programming, linear and semidefinite programming, and randomization. Each chapter in the first section is devoted to a single algorithmic technique applied to several different problems, with more sophisticated treatment in the second section. The book also covers methods for proving that optimization problems are hard to approximate. Designed as a textbook for graduate-level algorithm courses, it will also serve as a reference for researchers interested in the heuristic solution of discrete optimization problems.

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850,98 zł

Object-Oriented Discrete-Event Simulation with Java Springer, Berlin

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This book introduces the application of the Java programming language in discrete-event simulation. In addition, the fundamental concepts and practical simulation techniques for modeling different types of systems to study their general behavior and their performance are introduced. The approaches applied are the process interaction approach to discrete-event simulation and object-oriented modeling. Java is used as the implementation language and UML as the modeling language. The first offers several advantages compared to C++, the most important being thread handling, graphical user interfaces (GUI), and Web computing. The second language, UML (Unified Modeling Language), is the standard notation used today for modeling systems as a collection of classes, class relationships, objects, and object behavior. The book concentrates on object-oriented modeling and implementation aspects of simulation models using Java and practical simulation techniques. In addition, the book illustrates the dynamic behavior of systems using the various simulation models as case studies.

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