How to Implement Market Models Using VBA
How to Implement Market Models Using VBA makes solving complex valuation issues accessible to any financial professional with a taste for mathematics. With a focus on the clarity of code, this practical introductory guide includes chapters on VBA fundamentals and essential mathematical techniques, helping readers master the numerical methods to build an algorithm that can be used in a wide range of pricing problems. Coverage includes general algorithms, vanilla instruments, multi-asset instruments, yield curve models, interest rate exotics, and more, guiding readers thoroughly through pricing in the capital markets area. The companion website (http://implementmodinvba.com/) features additional VBA code and algorithmic techniques, and the interactive blog provides a forum for discussion of code with programmers and financial engineers, giving readers insight into the different applications and customisations possible for even more advanced problem solving. ...
How to Implement Market Models Using VBA makes solving complex valuation issues accessible to any financial professional with a taste for mathematics. With a focus on the clarity of code, this practical introductory guide includes chapters on VBA fundamentals and essential mathematical techniques, helping readers master the numerical methods to build an algorithm that can be used in a wide range of pricing problems. Coverage includes general algorithms, vanilla instruments, multi-asset instruments, yield curve models, interest rate exotics, and more, guiding readers thoroughly through pricing in the capital markets area. The companion website (http://implementmodinvba.com/) features additional VBA code and algorithmic techniques, and the interactive blog provides a forum for discussion of code with programmers and financial engineers, giving readers insight into the different applications and customisations possible for even more advanced problem solving. ...
MATLAB Recipes
Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. MATLAB Recipes: A Problem-Solution Approach is a practical reference for industry engineers using MATLAB to solve everyday problems. With this book you will review contemporary MATLAB coding including the latest language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. This book provides practical guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your line of work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm. ...
Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. MATLAB Recipes: A Problem-Solution Approach is a practical reference for industry engineers using MATLAB to solve everyday problems. With this book you will review contemporary MATLAB coding including the latest language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. This book provides practical guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your line of work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm. ...
OSPF: A Network Routing Protocol
Learn how routers network using the OSPF (Open Shortest Path First) protocol and unpick Dijkstra's Network Algorithm to see how OSPF performs the calculations to determine the shortest or most appropriate path between two routers. OSPF: A Network Routing Protocol dives deep into the OSPF protocol without sacrificing simplicity in language. All of this is done with running examples and illustrations to clarify concepts and enhance the enjoyment of networking. OSPF: A Network Routing Protocol is an absorbing, comprehensible account of OSPF, including the algorithm which is used for calculating its routes. While OSPF has traditionally been an organizational networking protocol, in these exciting times of Software Defined Networking (SDN), it has assumed an important role in the consolidated data center too. Now that the traditional distinctions between server and network roles are getting blurred, everyone in the data center needs to become familiar with networking and networking proto ...
Learn how routers network using the OSPF (Open Shortest Path First) protocol and unpick Dijkstra's Network Algorithm to see how OSPF performs the calculations to determine the shortest or most appropriate path between two routers. OSPF: A Network Routing Protocol dives deep into the OSPF protocol without sacrificing simplicity in language. All of this is done with running examples and illustrations to clarify concepts and enhance the enjoyment of networking. OSPF: A Network Routing Protocol is an absorbing, comprehensible account of OSPF, including the algorithm which is used for calculating its routes. While OSPF has traditionally been an organizational networking protocol, in these exciting times of Software Defined Networking (SDN), it has assumed an important role in the consolidated data center too. Now that the traditional distinctions between server and network roles are getting blurred, everyone in the data center needs to become familiar with networking and networking proto ...
Algorithms in a Nutshell, 2nd Edition
Creating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. This updated edition of Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs - with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. ...
Creating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. This updated edition of Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs - with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. ...
Distributed Graph Algorithms for Computer Networks
This hands-on textbook/reference presents a comprehensive review of key distributed graph algorithms for computer network applications, with a particular emphasis on practical implementation. Each chapter opens with a concise introduction to a specific problem, supporting the theory with numerous examples, before providing a list of relevant algorithms. These algorithms are described in detail from conceptual basis to pseudocode, complete with graph templates for the stepwise implementation of the algorithm, followed by its analysis. ...
This hands-on textbook/reference presents a comprehensive review of key distributed graph algorithms for computer network applications, with a particular emphasis on practical implementation. Each chapter opens with a concise introduction to a specific problem, supporting the theory with numerous examples, before providing a list of relevant algorithms. These algorithms are described in detail from conceptual basis to pseudocode, complete with graph templates for the stepwise implementation of the algorithm, followed by its analysis. ...
Python Algorithms, 2nd Edition
Python Algorithms, 2nd Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others. ...
Python Algorithms, 2nd Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others. ...
Genetic Programming Theory and Practice X
These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: evolutionary constraints, relaxation of selection mechanisms, diversity preservation strategies, flexing fitness evaluation, evolution in dynamic environments, multi-objective and multi-modal selection, foundations of evolvability, evolvable and adaptive evolutionary operators, foundation of injecting expert knowledge in evolutionary search, analysis of problem difficulty and required GP algorithm complexity, foundations in running GP on the cloud – communication, cooperation, flexible implementation, and ensemble methods. ...
These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: evolutionary constraints, relaxation of selection mechanisms, diversity preservation strategies, flexing fitness evaluation, evolution in dynamic environments, multi-objective and multi-modal selection, foundations of evolvability, evolvable and adaptive evolutionary operators, foundation of injecting expert knowledge in evolutionary search, analysis of problem difficulty and required GP algorithm complexity, foundations in running GP on the cloud – communication, cooperation, flexible implementation, and ensemble methods. ...
Reinforcement Learning
Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You'll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov's Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI before looking at Open AI Gym. You'll then learn about Swarm Intelligence with Python in terms of reinforcement learning. The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There's also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you'll delve into Google's Deep Mind and see scenarios where rein ...
Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You'll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov's Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI before looking at Open AI Gym. You'll then learn about Swarm Intelligence with Python in terms of reinforcement learning. The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There's also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you'll delve into Google's Deep Mind and see scenarios where rein ...
Text Analytics with Python
Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure; Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summa ...
Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure; Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summa ...
A Common-Sense Guide to Data Structures and Algorithms
Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. This book takes a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. Graphics and examples make these computer science concepts understandable and relevant. You can use these techniques with any language; examples in the book are in JavaScript, Python, and Ruby. Use Big O notation, the primary tool for evaluating algorithms, to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such a ...
Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. This book takes a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. Graphics and examples make these computer science concepts understandable and relevant. You can use these techniques with any language; examples in the book are in JavaScript, Python, and Ruby. Use Big O notation, the primary tool for evaluating algorithms, to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such a ...