Search results for "python programming for mathematics"
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R 580.00
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Methods of Applied Mathematics with a Software Overview
Broadly organized around the applications of Fourier analysis, "Methods of Applied Mathematics with a MATLAB Overview" covers both classical applications in partial differential equations and boundary value problems, as well as the concepts and methods associated to the Laplace, Fourier, and discrete transforms. Transform inversion problems are also examined, along with the necessary background in complex variables. A final chapter treats wavelets, short-time Fourier analysis, and geometrically-based transforms. The computer program MATLAB is emphasized throughout, and an introduction to MATLAB is provided in an appendix. Rich in examples, illustrations, and exercises of varying difficulty, this text can be used for a one- or two-semester course and is ideal for students in pure and applied mathematics, physics, and engineering.
R 3,627.00
Building and Solving Mathematical Programming Models
This book presents the construction and resolution of 50 practical optimization problems and covers an exceptionally wide range, including games-associated problems (Unblock Me, Sudokus), logistical problems, and problems concerning plant distribution, production, operations scheduling, management and resource allocation.The problems are divided into 5 difficulty levels. Problems in the first few levels are focused on learning the model construction methodology, while those in the last level include complex optimization environments. For each problem solution, the specific steps are illustrated, promoting reader comprehension.In addition, all the models are implemented in an optimization library, LINGO, their solutions have been analyzed and their correct construction has been verified. The book also includes a simple guide to implementing models in LINGO in a straightforward manner and in any input data format (text files, spreadsheets or databases).As an ideal companion to the author’s previously published work Modelling in Mathematical Programming, the book is intended as a basic tool for students of operations research, and for researchers in any advanced area involving mathematical programming.
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Finite Mathematics
Features step-by-step examples based on actual data and connects fundamental mathematical modeling skills and decision making concepts to everyday applicability Featuring key linear programming, matrix, and probability concepts, Finite Mathematics: Models and Applications emphasizes cross-disciplinary applications that relate mathematics to everyday life. The book provides a unique combination of practical mathematical applications to illustrate the wide use of mathematics in fields ranging from business, economics, finance, management, operations research, and the life and social sciences. In order to emphasize the main concepts of each chapter, Finite Mathematics: Models and Applications features plentiful pedagogical elements throughout such as special exercises, end notes, hints, select solutions, biographies of key mathematicians, boxed key principles, a glossary of important terms and topics, and an overview of use of technology. The book encourages the modeling of linear programs and their solutions and uses common computer software programs such as LINDO. In addition to extensive chapters on probability and statistics, principles and applications of matrices are included as well as topics for enrichment such as the Monte Carlo method, game theory, kinship matrices, and dynamic programming. Supplemented with online instructional support materials, the book features coverage including: Algebra SkillsMathematics of FinanceMatrix AlgebraGeometric SolutionsSimplex MethodsApplication ModelsSet and Probability RelationshipsRandom Variables and Probability DistributionsMarkov ChainsMathematical StatisticsEnrichment in Finite Mathematics An ideal textbook, Finite Mathematics: Models and Applications is intended for students in fields from entrepreneurial and economic to environmental and social science, including many in the arts and humanities.
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Python 3 for Machine Learning
This book is designed to provide the reader with basic Python3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fundamental concepts of machine learning. The sixth chapter is devoted to machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on NLP and RL. Keras-based code samples are included to supplement the theoretical discussion. The book also contains separate appendices for regular expressions, Keras, and TensorFlow 2.Features:Provides the reader withbasic Python3 programming concepts related to machine learningIncludes separate appendices for regular expressions, Keras, and TensorFlow 2
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Essential Programming for the Technical Artist
This book is based on a successful curriculum designed to elevate technical artists with no programming experience up to essential programming competency as quickly as possible. Instead of abstract, theoretical problems, the curriculum employs familiar applications encountered in real production environments to demonstrate each lesson.Written with artists in mind, this book introduces novice programmers to the advantageous world of Python programming with relevant and familiar examples. Any digital artists (not just technical artists) will find this book helpful in assisting with day-to-day production activities.Concentrating upon subjects relevant to the creation of computer graphic assets, this book introduces Python basics, functions, data types, object-oriented programming, exception handling, file processing, graphical user interface creation, PEP 8 standards, and regular expressions. Programming within the SideFX Houdini 3D animation software provides a familiar environment for artists to create and experiment with the covered Python topics.
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Test-Driven Development with Python
The third edition of this trusted guide demonstrates the practical advantages of test-driven development (TDD) with Python and describes how to develop a real web application. You'll learn how to write and run tests before building each part of your app and then develop the minimum amount of code required to pass those tests. The result? Clean code that works. In the process, author Harry Percival teaches software and web developers the basics of Django, Selenium, Git, JavaScript, and Mock libraries, along with current web development techniques. This book--updated for Python 3.14 and Django 4--clearly demonstrates how TDD encourages simple designs and inspires confidence. Fully updated, this third edition addresses: The TDD workflow, including the unit test/code cycle and refactoring Unit tests for classes and functions and functional tests for user interactions within the browser Mock objects and the pros and cons of isolated versus integrated tests Testing and automation of deployments with a staging server Tests applied to the third-party plug-ins you integrate into your site Automatic tests using a continuous integration environment Using TDD to build a REST API with a JavaScript frontend interface
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R 519.00
Beginning Mathematics for Chemistry
Many first year undergraduate chemistry students are daunted by the mathematical content of their courses. Mathematics in chemistry often presents an obstacle, preventing the student from grasping the chemical concepts and real ideas that lie behind the maths. This excellent workbook will help students to overcome this problem, which cannot be solved with a textbook. It aims to be a mathematics `toolkit' rather than a formal mathematics course. This flexibilityallows the student to study alone or in a group. The material covered is taken from examples of first year chemistry courses in approximately 6 x 3 hour sessions, providing a more comfortable and familiar way to learn. This workbook meets the needs of the student and is the best introduction tomathematics in chemistry available.
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Fuzzy Relational Mathematical Programming
This book summarizes years of research in the field of fuzzy relational programming, with a special emphasis on geometric models. It discusses the state-of-the-art in fuzzy relational geometric problems, together with key open issues that must be resolved to achieve a more efficient application of this method. Though chiefly based on research conducted by the authors, who were the first to introduce fuzzy geometric problems, it also covers important findings obtained in the field of linear and non-linear programming. Thanks to its balance of basic and advanced concepts, and its wealth of practical examples, the book offers a valuable guide for both newcomers and experienced researcher in the fields of soft computing and mathematical optimization.
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Python for Secret Agents - Volume II
Gather, analyze, and decode data to reveal hidden facts using Python, the perfect tool for all aspiring secret agentsAbout This Book• Discover the essential features of Python programming: statements, variables, expressions, and many of the built-in data types• Use Python's standard library to do more sophisticated data gathering and analysis• Written by a Python programming expert, with over 35 years' experience as a consultant, teacher, author and software developerWho This Book Is ForThis book is for Secret Agents who have some exposure to Python. Our focus is on the Field Agents who are ready to do more sophisticated and complex programming in Python. We'll stick to simple statistics for the most part. A steady hand with a soldering iron is not required, but a skilled field agent should be able to assemble a working Arduino circuit to gather their own sensor data.What You Will Learn• Upgrade Python to the latest version and discover its latest and greatest tools• Use Python libraries to extract data from log files that are designed more for people to read than for automated analysis• Summarize log files and extract meaningful information• Gather data from social networking sites and leverage your experience of analyzing log files to summarize the data you find• Extract text and images from social networking sites• Parse the complex and confusing data structures in a PDF file to extract meaningful text that we can analyze• Connect small, intelligent devices to our computer to use them as remote sensors• Use Python to analyze measurements from sensors to calibrate them and use sensors efficientlyIn DetailPython is easy to learn and extensible programming language that allows any manner of secret agent to work with a variety of data. Agents from beginners to seasoned veterans will benefit from Python's simplicity and sophistication. The standard library provides numerous packages that move beyond simple beginner missions. The Python ecosystem of related packages and libraries supports deep information processing.This book will guide you through the process of upgrading your Python-based toolset for intelligence gathering, analysis, and communication. You'll explore the ways Python is used to analyze web logs to discover the trails of activities that can be found in web and database servers. We'll also look at how we can use Python to discover details of the social network by looking at the data available from social networking websites.Finally, you'll see how to extract history from PDF files, which opens up new sources of data, and you'll learn about the ways you can gather data using an Arduino-based sensor device.Style and approachEach chapter will include a background briefing that covers an essential Python technology. After some in-depth exploration of the features, the chapter will conclude with a mission that is a concrete application of the Python tools and techniques covered.
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Python Illustrated
Learn Python coding concepts the fun way through humour, storytelling, and beginner-friendly examples that make your first step into the world of Python programming enjoyableKey FeaturesFollow an adorable, illustrated teaching cat with sharp coding instincts as your guideBuild confidence and coding skills with step-by-step explanations that gradually increase your understandingReinforce your learning through mini-projects and exercises at the end of every chapterPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThis is not your average Python programming book, because the world doesn’t need another one of those. Instead, it’s an illustrated, fun, and hands-on guide that treats learning Python like the adventure it should be. It’s designed especially for beginners who want to understand how code works without getting overwhelmed. You’ll be guided by a cheeky, know-it-all cat who’s surprisingly good at teaching Python from scratch. Don’t worry about going through it alone; a slightly moody dachshund dog is your study buddy, learning right alongside you. Each chapter introduces a core programming concept, explains it with a playful twist, and reinforces it through human-friendly examples, analogies, and exercises. Whether you’re a software professional or someone who’s never written a single line of code, this book will help you build real Python coding skills… and even enjoy the process (shocking, right?). Forget dry tutorials and walls of text. Python Illustrated speaks to visual learners, creative thinkers, cat lovers, dog lovers, and anyone who prefers their learning with a dash of humor. From writing your first function to understanding object-oriented programming, you’ll build a solid foundation in Python (without the usual headaches). What you will learnSet up Python and write your first programUnderstand variables, data types, and conditional statementsUse loops, lists, dictionaries, and tuples to handle data efficientlyWrite and use functions to create reusable codeManage files and understand object-oriented programming and inheritanceDebug your Python code to ensure it works flawlesslyDiscover how you can keep learning and building beyond this bookWho this book is forThis book is ideal for anyone with a sense of humour who’s new to Python or programming in general. It takes a step-by-step hands-on approach that will work for anyone with a practical mindset. Whether you're a student or a professional developer looking to expand your skill set, this book offers a comprehensive and enjoyable learning experience.
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Elementary Numerical Mathematics for Programmers and Engineers
This book covers the basics of numerical methods. Avoiding the definition-theorem-proof style, it instead focuses on numerical examples and simple pseudo-codes.The text begins with a chapter on floating point arithmetic before moving on to discuss norms, conditions numbers, solutions of systems of equations, the least squares problem, eigenvalue problems, interpolation, numerical integration, ordinary differential equations, optimization (including a detailed case study), and practical error estimations. Exercises (partly in MATLAB) are provided at the end of each chapter. Suitable for readers with minimal mathematical knowledge, the book not only offers an elementary introduction to numerical mathematics for programmers and engineers but also provides supporting material for students and teachers of mathematics.
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Practical Python Programming for IoT
Leverage Python and Raspberry Pi to create complex IoT applications capable of creating and detecting movement and measuring distance, light, and a host of other environmental conditionsKey FeaturesLearn the fundamentals of electronics and how to integrate them with a Raspberry PiUnderstand how to build RESTful APIs, WebSocket APIs, and MQTT-based applicationsExplore alternative approaches to structuring IoT applications with PythonBook DescriptionThe age of connected devices is here, be it fitness bands or smart homes. It's now more important than ever to understand how hardware components interact with the internet to collect and analyze user data. The Internet of Things (IoT), combined with the popular open source language Python, can be used to build powerful and intelligent IoT systems with intuitive interfaces. This book consists of three parts, with the first focusing on the "Internet" component of IoT. You'll get to grips with end-to-end IoT app development to control an LED over the internet, before learning how to build RESTful APIs, WebSocket APIs, and MQTT services in Python. The second part delves into the fundamentals behind electronics and GPIO interfacing. As you progress to the last part, you'll focus on the "Things" aspect of IoT, where you will learn how to connect and control a range of electronic sensors and actuators using Python. You'll also explore a variety of topics, such as motor control, ultrasonic sensors, and temperature measurement. Finally, you'll get up to speed with advanced IoT programming techniques in Python, integrate with IoT visualization and automation platforms, and build a comprehensive IoT project. By the end of this book, you'll be well-versed with IoT development and have the knowledge you need to build sophisticated IoT systems using Python.What you will learnUnderstand electronic interfacing with Raspberry Pi from scratchGain knowledge of building sensor and actuator electronic circuitsStructure your code in Python using Async IO, pub/sub models, and moreAutomate real-world IoT projects using sensor and actuator integrationIntegrate electronics with ThingSpeak and IFTTT to enable automationBuild and use RESTful APIs, WebSockets, and MQTT with sensors and actuatorsSet up a Raspberry Pi and Python development environment for IoT projectsWho this book is forThis IoT Python book is for application developers, IoT professionals, or anyone interested in building IoT applications using the Python programming language. It will also be particularly helpful for mid to senior-level software engineers who are experienced in desktop, web, and mobile development, but have little to no experience of electronics, physical computing, and IoT.
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Computer-Assisted Analysis System for Mathematical Programming Models and Solutions
Welcome to ANALYZE, designed to provide computer assistance for analyzing linear programs and their solutions. Chapter 1 gives an overview of ANALYZE and how to install it. It also describes how to get started and how to obtain further documentation and help on-line. Chapter 2 reviews the forms of linear programming models and describes the syntax of a model. One of the routine, but important, functions of ANALYZE is to enable convenient access to rows and columns in the matrix by conditional delineation. Chapter 3 illustrates simple queries, like DISPLAY, LIST, and PICTURE. This chapter also introduces the SUBMAT command level to define any submatrix by an arbitrary sequence of additions, deletions and reversals. Syntactic explanations and a schema view are also illustrated. Chapter 4 goes through some elementary exercises to demonstrate computer assisted analysis and introduce additional conventions of the ANALYZE language. Besides simple queries, it demonstrates the INTERPRT command, which automates the analysis process and gives English explanations of results. The last 2 exercises are diagnoses of elementary infeasible instances of a particular model. Chapter 5 progresses to some advanced uses of ANALYZE. The first is blocking to obtain macro views of the model and for finding embedded substructures, like a netform. The second is showing rates of substitution described by the basic equations. Then, the use of the REDUCE and BASIS commands are illustrated for a variety of applications, including solution analysis, infeasibility diagnosis, and redundancy detection.
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Python 3 Object-Oriented Programming
Uncover modern Python with this guide to Python data structures, design patterns, and effective object-oriented techniquesKey FeaturesIn-depth analysis of many common object-oriented design patterns that are more suitable to Python's unique styleLearn the latest Python syntax and librariesExplore abstract design patterns and implement them in Python 3.8Book DescriptionObject-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. This third edition of Python 3 Object-Oriented Programming fully explains classes, data encapsulation, and exceptions with an emphasis on when you can use each principle to develop well-designed software. Starting with a detailed analysis of object-oriented programming, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. You will learn how to create maintainable applications by studying higher level design patterns. The book will show you the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems, unittest and pytest, will be introduced in this book. You'll get a comprehensive introduction to Python's concurrent programming ecosystem. By the end of the book, you will have thoroughly learned object-oriented principles using Python syntax and be able to create robust and reliable programs confidently.What you will learnImplement objects in Python by creating classes and defining methodsGrasp common concurrency techniques and pitfalls in Python 3Extend class functionality using inheritanceUnderstand when to use object-oriented features, and more importantly when not to use themDiscover what design patterns are and why they are different in PythonUncover the simplicity of unit testing and why it's so important in PythonExplore concurrent object-oriented programmingWho this book is forIf you're new to object-oriented programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply OOP in Python, this is the book for you. If you are an object-oriented programmer for other languages or seeking a leg up in the new world of Python 3.8, you too will find this book a useful introduction to Python. Previous experience with Python 3 is not necessary.
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Python for Signal Processing
This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to “experiment and learn” as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future. For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.
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R Programming and Its Applications in Financial Mathematics
This book provides an introduction to R programming and a summary of financial mathematics.It is not always easy for graduate students to grasp an overview of the theory of finance in an abstract form. For newcomers to the finance industry, it is not always obvious how to apply the abstract theory to the real financial data they encounter. Introducing finance theory alongside numerical applications makes it easier to grasp the subject.Popular programming languages like C++, which are used in many financial applications are meant for general-purpose requirements. They are good for implementing large-scale distributed systems for simultaneously valuing many financial contracts, but they are not as suitable for small-scale ad-hoc analysis or exploration of financial data. The R programming language overcomes this problem. R can be used for numerical applications including statistical analysis, time series analysis, numerical methods for pricing financial contracts, etc.This book provides an overview of financial mathematics with numerous examples numerically illustrated using the R programming language.
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Oxford Mathematics Primary Years Programme Practice and Mastery Book 1
Provide opportunities to consolidate mathematical knowledge and skills and help learners to grow in confidence and independence with this colourful, inquiry-based Practice and Mastery Book.· Cover the five strands of Number, Pattern and Function, Measurement, Shape and Space, and Data Handling· Provide comprehensive coverage of the PYP Mathematics Scope and Sequence· Support and extend learning through reinforcement activities· Encourage learners to explore and apply knowledge using real-world problems
R 559.00
Oxford Mathematics Primary Years Programme Practice and Mastery Book 6
Provide opportunities to consolidate mathematical knowledge and skills and help learners to grow in confidence and independence with this colourful, inquiry-based Practice and Mastery Book.· Cover the five strands of Number, Pattern and Function, Measurement, Shape and Space, and Data Handling· Provide comprehensive coverage of the PYP Mathematics Scope and Sequence· Support and extend learning through reinforcement activities· Encourage learners to explore and apply knowledge using real-world problems
R 793.00
Essential Mathematics for Convex Optimization
With an emphasis on timeless essential mathematical background for optimization, this textbook provides a comprehensive and accessible introduction to convex optimization for students in applied mathematics, computer science, and engineering. Authored by two influential researchers, the book covers both convex analysis basics and modern topics such as conic programming, conic representations of convex sets, and cone-constrained convex problems, providing readers with a solid, up-to-date understanding of the field. By excluding modeling and algorithms, the authors are able to discuss the theoretical aspects in greater depth. Over 170 in-depth exercises provide hands-on experience with the theory, while more than 30 'Facts' and their accompanying proofs enhance approachability. Instructors will appreciate the appendices that cover all necessary background and the instructors-only solutions manual provided online. By the end of the book, readers will be well equipped to engage with state-of-the-art developments in optimization and its applications in decision-making and engineering.
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Learning Python for Forensics
Learn the art of designing, developing, and deploying innovative forensic solutions through PythonAbout This Book• This practical guide will help you solve forensic dilemmas through the development of Python scripts• Analyze Python scripts to extract metadata and investigate forensic artifacts• Master the skills of parsing complex data structures by taking advantage of Python librariesWho This Book Is ForIf you are a forensics student, hobbyist, or professional that is seeking to increase your understanding in forensics through the use of a programming language, then this book is for you.You are not required to have previous experience in programming to learn and master the content within this book. This material, created by forensic professionals, was written with a unique perspective and understanding of examiners who wish to learn programmingWhat You Will Learn• Discover how to perform Python script development• Update yourself by learning the best practices in forensic programming• Build scripts through an iterative design• Explore the rapid development of specialized scripts• Understand how to leverage forensic libraries developed by the community• Design flexibly to accommodate present and future hurdles• Conduct effective and efficient investigations through programmatic pre-analysis• Discover how to transform raw data into customized reports and visualizationsIn DetailThis book will illustrate how and why you should learn Python to strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. The tutorials use an interactive design, giving you experience of the development process so you gain a better understanding of what it means to be a forensic developer.Each chapter walks you through a forensic artifact and one or more methods to analyze the evidence. It also provides reasons why one method may be advantageous over another. We cover common digital forensics and incident response scenarios, with scripts that can be used to tackle case work in the field. Using built-in and community-sourced libraries, you will improve your problem solving skills with the addition of the Python scripting language. In addition, we provide resources for further exploration of each script so you can understand what further purposes Python can serve. With this knowledge, you can rapidly develop and deploy solutions to identify critical information and fine-tune your skill set as an examiner.Style and approachThe book begins by instructing you on the basics of Python, followed by chapters that include scripts targeted for forensic casework. Each script is described step by step at an introductory level, providing gradual growth to demonstrate the available functionalities of Python.
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Programming: A Primer - Coding For Beginners
Have you ever wanted to learn how to program but never found quite the right book to get you started? Programming: A Primer gets you going straight away with the fundamentals of what programming is, basic programming with Python and the fundamental aspects of practical web development. In this book, you'll learn about:Programming: A Primer offers an easy way into coding for anyone with an interest in using technology to solve problems, whether a school or new undergraduate computer science student or a working professional. It gives everyone, regardless of background, the ideal foundations and motivation needed to get to grips with programming.A companion website can be found here: .
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C++ for Financial Mathematics
If you know a little bit about financial mathematics but don’t yet know a lot about programming, then C++ for Financial Mathematics is for you.C++ is an essential skill for many jobs in quantitative finance, but learning it can be a daunting prospect. This book gathers together everything you need to know to price derivatives in C++ without unnecessary complexities or technicalities. It leads the reader step-by-step from programming novice to writing a sophisticated and flexible financial mathematics library. At every step, each new idea is motivated and illustrated with concrete financial examples.As employers understand, there is more to programming than knowing a computer language. As well as covering the core language features of C++, this book teaches the skills needed to write truly high quality software. These include topics such as unit tests, debugging, design patterns and data structures. The book teaches everything you need to know to solve realistic financial problems in C++. It can be used for self-study or as a textbook for an advanced undergraduate or master’s level course.
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R 422.46
Distributed Programming
Distributed Programming: Theory and Practice presents a practical and rigorous method to develop distributed programs that correctly implement their specifications. The method also covers how to write specifications and how to use them. Numerous examples such as bounded buffers, distributed locks, message-passing services, and distributed termination detection illustrate the method. Larger examples include data transfer protocols, distributed shared memory, and TCP network sockets. Distributed Programming: Theory and Practice bridges the gap between books that focus on specific concurrent programming languages and books that focus on distributed algorithms. Programs are written in a "real-life" programming notation, along the lines of Java and Python with explicit instantiation of threads and programs. Students and programmers will see these as programs and not "merely" algorithms in pseudo-code. The programs implement interesting algorithms and solve problems that are large enough to serve as projects in programming classes and software engineering classes. Exercises and examples are included at the end of each chapter with on-line access to the solutions. Distributed Programming: Theory and Practice is designed as an advanced-level text book for students in computer science and electrical engineering. Programmers, software engineers and researchers working in this field will also find this book useful.
R 1,572.21
R 611.00
