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Introduction to Scientific Computing with MATLAB® and Python Tutorials
This textbook is written for the first introductory course on scientific computing. It covers elementary numerical methods for linear systems, root finding, interpolation, numerical integration, numerical differentiation, least squares problems, initial value problems and boundary value problems. It includes short Matlab and Python tutorials to quickly get students started on programming. It makes the connection between elementary numerical methods with advanced topics such as machine learning and parallel computing.This textbook gives a comprehensive and in-depth treatment of elementary numerical methods. It balances the development, implementation, analysis and application of a fundamental numerical method by addressing the following questions.•Where is the method applied?•How is the method developed?•How is the method implemented?•How well does the method work?The material in the textbook is made as self-contained and easy-to-follow as possible with reviews and remarks. The writing is kept concise and precise. Examples, figures, paper-and-pen exercises and programming problems are deigned to reinforce understanding of numerical methods and problem-solving skills.
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Python Programming and Numerical Methods
Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving techniques through the use of numerical methods and the Python programming language. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level that allows students to quickly apply results in practical settings.
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Introduction to Generative AI with Julia and Python
Elevate your coding capabilities and gain the skills necessary for maximized performance and career opportunities in the field of Artificial Intelligence. This book is a step-by-step guide designed to equip software engineers with solid foundation of Generative AI basics. The book begins by introducing Generative AI using Google Colab to establish a solid foundation, before demonstrating how to leverage Python and Julia's AI capabilities to construct Artificial Neural Networks. You'll then explore advanced AI models, such as variational autoencoders, in order to generative images and text. Author Pierluigi Riti not only navigates the complexities of this emerging topic but fills a crucial gap by guiding software engineers through theory before leading them to produce different types of models using only free resources. What You Will Learn Acquire a solid foundation of Generative AI basics.Utilize the capabilities of Python and Julia to constructure Artificial Neural NetworksExplore advanced AI models including variational autoencoders, to generate images Survey different architectures for AI and utilize free resources to produce different AI Who This Book Is For Programmers new to artificial intelligence, but with a fundamental grasp of Python.
R 1,368.00
R 2,127.20
Introduction to Programming Using Processing
Written in an informal, conversational, and humorous style, Introduction to Programming Using Processing makes learning programming a fun experience. It is almost certainly the only programming textbook in the world with references to Jurassic Park, NCIS, Chuck Norris, and Gamera! The freely-available Processing language is ideal for a first course in programming. The simple-to-access graphics and multimedia capabilities of the language let students develop eye-catching, animated programs, instead of traditional programs that print text to the console. Introduction to Programming Using Processing takes a "classes-later" approach, focusing on basics, using objects, selection, iteration, top-down design, and arrays, before writing classes. Every example is presented in the context of the RADIS (Requirements / Analyze / Design / Implement / Support) framework, with considerable attention paid to design. Other positive habits, like good commenting practice and coding style, are emphasized as well.
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Introduction to Mathematical Modeling and Computer Simulations
Introduction to Mathematical Modeling and Computer Simulations, Second Edition continues to serve as an engaging and accessible textbook for undergraduates studying mathematical modeling and computer simulations. The book is heavily focussed on applications, and so may have a particular appeal to applied mathematicians, engineers, and others working in applied quantitative disciplines. The book may also be useful as a reference text for reference text for early-career stage practitioners.New to this Edition:A new chapter on Machine Learning and Data Analysis in order to account for recent developments in the field.Chapter 9, ‘Asymptotic Methods in Composites’, has been entirely re-written to make it more consistent with industry and scientific standards.Includes an elementary introduction to programming in Python language.The Jupyter notebooks with examples for Chapter 10 and Appendix A are available for a download from www.Routledge.com/9781032661513.
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Introduction to Radar Using Python and MATLAB
"A well-constructed and concisely written book, incorporating a balanced combination of textual explanations and well-presented mathematical descriptions, which serves both as an introduction to many important aspects of radar but also as an extensive exercise in the usage and application of both the MATLAB and Python programming applications. It is eminently readable and understandable. I assess that it is probably most relevant to post graduate student scientists and engineers requiring a moderately detailed understanding of aspects of radar with a view to practical applications”Aerospace Magazine This comprehensive resource provides readers with the tools necessary to perform analysis of various waveforms for use in radar systems. It provides information about how to produce synthetic aperture (SAR) images by giving a tomographic formulation and implementation for SAR imaging. Tracking filter fundamentals, and each parameter associated with the filter and how each affects tracking performance are also presented. Various radar cross section measurement techniques are covered, along with waveform selection analysis through the study of the ambiguity function for each particular waveform from simple linear frequency modulation (LFM) waveforms to more complicated coded waveforms. The text includes the Python tool suite, which allows the reader to analyze and predict radar performance for various scenarios and applications. Also provided are MATLAB® scripts corresponding to the Python tools. The software includes a user-friendly graphical user interface (GUI) that provides visualizations of the concepts being covered. Users have full access to both the Python and MATLAB source code to modify for their application. With examples using the tool suite are given at the end of each chapter, this text gives readers a clear understanding of how important target scattering is in areas of target detection, target tracking, pulse integration, and target discrimination.
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Python Automation For Dummies
Streamline Your Workflow and Boost Productivity with Python Automation In today's workplaces, there's a high demand for know-how on the Python programming language, especially for writing time-saving scripts that can simplify routine work tasks. Python Automation For Dummies delivers, with simple explanations of how you can use Python to automatically wrangle data files, manage media files, create shortcuts, find and organize web data, and even analyze social media for trends. With this easy-to-follow Dummies guide, you can upskill, expand your productivity, and speed up the process of generating data-driven insights. You'll even learn to enhance your Python automations with AI, for workflows that are faster and smarter. Review the basics of Python coding and follow steps for automating all sorts of tasksManage large file sets, organize and analyze data, and speed up research processesAutomate scheduling and other time-consuming tasks—and optimize work with AIFree up time and resources by automating routine work, so you can foucs on more important issues This is a great Dummies resource for Python developers interested in applying the popular coding language to make workflows more efficient.
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Introduction to Parallel Programming
An introduction to parallel programming with openmpi using C. It is written so that someone with even a basic understanding of programming can begin to write mpi based parallel programs.
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Expert Python Programming -
Become an ace Python programmer by learning best coding practices and advance-level concepts with Python 3.5About This Book• Based on the latest stable version of Python (version 3.5)• Creating well manageable code that will run in various environments with different sets of dependencies• Packed with advanced concepts and best practices to write efficient Python codeWho This Book Is ForThe book would appeal to web developers and Python programmers who want to start using version 3.5 and write code efficiently. Basic knowledge of Python programming is expected.What You Will Learn• Conventions and best practices that are widely adopted in the python community• Package python code effectively for community and production use• Easy and lightweight ways to automate code deployment on remote systems• Improve your code's quality, reliability, and performance• Write concurrent code in python• Extend python with code written in different languagesIn DetailPython is a dynamic programming language, used in a wide range of domains by programmers who find it simple, yet powerful. Even if you find writing Python code easy, writing code that is efficient and easy to maintain and reuse is a challenge.The focus of the book is to familiarize you with common conventions, best practices, useful tools and standards used by python professionals on a daily basis when working with code.You will begin with knowing new features in Python 3.5 and quick tricks for improving productivity. Next, you will learn advanced and useful python syntax elements brought to this new version. Using advanced object-oriented concepts and mechanisms available in python, you will learn different approaches to implement metaprogramming. You will learn to choose good names, write packages, and create standalone executables easily.You will also be using some powerful tools such as buildout and vitualenv to release and deploy the code on remote servers for production use. Moving on, you will learn to effectively create Python extensions with C, C++, cython, and pyrex. The important factors while writing code such as code management tools, writing clear documentation, and test-driven development are also covered.You will now dive deeper to make your code efficient with general rules of optimization, strategies for finding bottlenecks, and selected tools for application optimization.By the end of the book, you will be an expert in writing efficient and maintainable code.Style and approach An easy-to-follow guide that covers industry followed best practices in Python programming
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R 165.00
Theoretical Introduction to Programming
Including easily digested information about fundamental techniques and concepts in software construction, this book is distinct in unifying pure theory with pragmatic details. Driven by generic problems and concepts, with brief and complete illustrations from languages including C, Prolog, Java, Scheme, Haskell and HTML.This book is intended to be both a how-to handbook and easy reference guide. Discussions of principle, worked examples and exercises are presented. All concepts outside introductory programming are explained with clear demarcation and dependencies so the experienced programmer can quickly locate material. Readable in a linear manner, with short mono-thematic to encourage dipping and reference. Also included are sections on open problems in software theory and practice.While little other than a novice programmer's knowledge is explicitly assumed, a certain conceptual maturity, either through commercial programming or academic training is required – each language is introduced and explained briefly as needed.
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Bioinformatics Programming Using Python
Through many examples and exercises, this book helps simplify bioinformatics programming using Python. It's an ideal guide for biologists who want to learn either basic scripting or substantial programming for various computational tasks, and for programmers who want to learn bioinformatics programming. "Bioinformatics Programming Using Python" can be used as a reference, for self-instruction, or as a companion book to help you through undergraduate courses in computer science, biology, and other life sciences. With the level of detail this book provides, it's also perfect for Professional Master's graduate courses in Bioinformatics.
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Python Programming for Mathematics
Python Programming for Mathematics focuses on the practical use of the Python language in a range of different areas of mathematics. Through fifty-five exercises of increasing difficulty, the book provides an expansive overview of the power of using programming to solve complex mathematical problems.This book is intended for undergraduate and graduate students who already have learned the basics of Python programming and would like to learn how to apply that programming skill in mathematics.FeaturesInnovative style that teaches programming skills via mathematical exercises.Ideal as a main textbook for Python for Mathematics courses, or as a supplementary resource for Numerical Analysis and Scientific Computing courses.
R 2,454.00
Introduction to Programming with ActionScript 3.0
This new full-color, multimedia-focused text provides a CS1 level introduction to computer programming by employing an example-based methodology involving animation, sound, graphics, and interactivity. As the multimedia language associated with Adobe� Flash�, ActionScript 3.0 offers a more compelling introduction to the world of programming than other standard programming languages, yet is powerful and comprehensive enough to provide a complete introduction to all the foundational concepts. By using the Flash environment, this book presents programming concepts that are relevant to multimedia-focused games and applications and is the ideal resource for those interested in building visually rich and interactive applications.An Introduction to Programming with ActionScript 3.0 satisfies ACM guidelines for a first course in a computer science curriculum and covers all of the key topics required for any introductory level programming course: program analysis and design, data types, selective and iterative control structures, functions, arrays, and classes. In addition, it covers ActionScript’s powerful ability to construct complex and interactive animations using graphics and sounds. Through programming, this text exposes readers to the problem solving and critical thinking skills required for effective participation in the digital world.An Introduction to Programming with ActionScript 3.0 is ideal for students interested in learning crucial programming concepts for which technology, arts, and media converge. It is also highly recommended for multimedia programmers, interactive artists, game designers, and innovative web application developers.Download the latest version of Flash here: https://get.adobe.com/flashplayer/Preview Content Now! Look to the Samples tab below to preview chapter 5
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Competitive Programming in Python
Want to kill it at your job interview in the tech industry? Want to win that coding competition? Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. Readers can expect to master 128 algorithms in Python and discover the right way to tackle a problem and quickly implement a solution of low complexity. Classic problems like Dijkstra's shortest path algorithm and Knuth-Morris-Pratt's string matching algorithm are featured alongside lesser known data structures like Fenwick trees and Knuth's dancing links. The book provides a framework to tackle algorithmic problem solving, including: Definition, Complexity, Applications, Algorithm, Key Information, Implementation, Variants, In Practice, and Problems. Python code included in the book and on the companion website.
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Introduction to Programming Using Visual Basic
For courses in Visual Basic Programming From the Beginning: A Comprehensive Introduction to Visual Basic Programming Schneider’s Introduction to Programming Using Visual Basic, Tenth Edition brings continued refinement to a textbook praised in the industry since 1991. A favorite for both instructors and students, Visual Basic 2015 is designed for readers with no prior computer programming experience. Schneider introduces a problem-solving strategy early in the book and revisits it throughout allowing you to fully develop logic and reasoning. A broad range of real-world examples, section-ending exercises, case studies and programming projects gives you a more hands-on experience than any other Visual Basic book on the market. The Tenth Edition keeps the pace with modern programming methodology while incorporating current content and practices. Each chapter is rich yet concise due to to the author’s focus on developing chapters around crucial subjects rather than covering too many topics superficially. The amount and the range of projects provided in the text offer flexibility to adapt the course according to the interests and abilities of the readers. Some programming projects in later chapters can be assigned as end-of-the-semester projects. Also available with MyProgrammingLabTM. MyProgrammingLab is an online learning system designed to engage students and improve results. MyProgrammingLab consists of a set of programming exercises correlated to specific Pearson CS1/Intro to Programming textbooks. Through practice exercises and immediate, personalized feedback, MyProgrammingLab improves the programming competence of beginning students who often struggle with the basic concepts of programming languages. Interactive Practice providesfirst-hand programming experience in an interactive online environment.Error Messages for Incorrect Answers give studentsimmediate personalized feedback. The error messages include both the feedback from the compiler and plain English interpretations of likely causes for the incorrect answer.Step-by-step VideoNote Tutorials enhance the programming concepts presented in your Pearson textbook by allowing students to view the entire problem-solving process outside of the classroom–when they need help the most.Pearson eText gives students access to their textbook anytime, anywhere. In addition to note taking, highlighting, and bookmarking, the Pearson eText offers interactive and sharing features. Rich media options let students watch lecture and example videos as they read or do their homework. Instructors can share their comments or highlights, and students can add their own, creating a tight community of learners in your class.The Pearson eText companion app allows existing subscribers to access their titles on an iPad or Android tablet for either online or offline viewing.Dynamic grading and assessment provide auto-grading of student assignments, saving you time and offering students immediate learning opportunities:
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Introduction to Modern Scientific Programming and Numerical Methods
The ability to use computers to solve mathematical relationships is a fundamental skill for anyone planning a career in science or engineering. For this reason, numerical analysis is part of the core curriculum for just about every undergraduate physics and engineering department. But for most physics and engineering students, practical programming is a self-taught process.This book introduces the reader not only to the mathematical foundation but also to the programming paradigms encountered in modern hybrid software-hardware scientific computing. After completing the text, the reader will be well-versed in the use of different numerical techniques, programming languages, and hardware architectures, and will be able to select the appropriate software and hardware tool for their analysis.It can serve as a textbook for undergraduate courses on numerical analysis and scientific computing courses within engineering and physical sciences departments. It will also be a valuable guidebook for researchers with experimental backgrounds interested in working with numerical simulations, or for any new personnel working in scientific computing or data analysis.Key Features:• Includes examples of solving numerical problems in multiple programming languages, including MATLAB, Python, Fortran, C++, Arduino, Javascript, and Verilog.• Provides an introduction to modern high-performance computing technologies including multithreading, distributed computing, GPUs, microcontrollers, FPGAs, and web "cloud computing".• Contains an overview of numerical techniques not found in other introductory texts including particle methods, finite volume and finite element methods, Vlasov solvers, and molecular dynamics.Companions websites for this book can be accessed at https://plasmasimulationsbyexample.com/ and https://www.scientificprogrammingbook.com/.Lubos Brieda holds a Ph.D. in Aerospace and Mechanical Aerospace Engineering from the George Washington University in Washington, D.C., USA and an M.Sc. in Aerospace and Ocean Engineering from Virginia Tech in Blacksburg, VA, USA. He is the president of Particle in Cell Consulting, LLC, Westlake Village, CA, USA, while also serving as a part-time lecturer in the Department of Astronautical Engineering at University of Southern California, Los Angeles, CA. Dr. Brieda is the author of numerous simulation codes utilized by the aerospace and plasma modeling communities. Additionally, he maintains an online blog found at particleincell.com/blog focusing on scientific computing and since 2014 he has been teaching online courses on plasma simulations through his website.Joseph Wang is a Professor of Astronautics and Aerospace and Mechanical Engineering at the University of Southern California. Prof. Wang received his Ph.D in Aeronautics and Astronautics from Massachusetts Institute of Technology in 1991. Prof. Wang conducts research in computational physics, space technology, and space and planetary science. He and his students have
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Asynchronous Programming in Python
Take a practical journey through the core principles, concepts, and applications of asynchronous programming in Python across real-world environments and technologies.Key FeaturesUnderstand core principles and theory behind async programming in PythonMeasure the impact of async techniques in practical, real-world use casesApply async patterns in software design and data-oriented architecturesBook DescriptionAsynchronous programming is one of the most effective but often misunderstood techniques for building fast, scalable, and responsive systems in Python. While it can significantly improve performance, efficiency, and sustainability, using async without a clear understanding of its trade-offs can lead to fragile designs and hard-to-debug issues.This book offers a structured approach to applying asynchronous programming in Python. It begins with a conceptual framework to help you distinguish between synchronous and asynchronous execution models, and shows how async relates to other concurrency strategies such as multithreading and multiprocessing. From there, you will explore the core tools available for building async applications in Python.You will also learn how to measure the impact of async programming in practical scenarios, profile and debug asynchronous code, and evaluate performance improvements using real-world metrics. The final chapters focus on applying async techniques to common cloud-based systems, such as web frameworks, database interactions, and data-pipelines tools.Designed for developers looking to apply async programming with confidence, this book blends real-world examples with core concepts to help you write efficient, maintainable Python code.What you will learnUse generators, coroutines and async/await to build scalable Python functionsExplore event loops to manage concurrency and orchestrate async flowCompare concurrency models to choose the right async strategyOptimize I/O-intensive programs to improve system throughput and efficiencyBuild async services using real-world APIs and popular Python librariesApply structured concurrency and design patterns for cleaner async designTest and debug async Python code to ensure reliability and stabilityWho this book is forThis book will help Python developers who want to understand and apply the asynchronous programming model in application development, data analysis, and orchestration scenarios. Junior developers, data engineers,, and tech leads will also benefit from the application design examples.
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Advanced Python Programming
Write fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge librariesKey FeaturesBenchmark, profile, and accelerate Python programs using optimization toolsScale applications to multiple processors with concurrent programmingMake applications robust and reusable using effective design patternsBook DescriptionPython's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages.In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level.This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models.The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming.You'll also understand the common problems that cause undesirable behavior in concurrent programs.Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable.By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.What you will learnWrite efficient numerical code with NumPy, pandas, and XarrayUse Cython and Numba to achieve native performanceFind bottlenecks in your Python code using profilersOptimize your machine learning models with JAXImplement multithreaded, multiprocessing, and asynchronous programsSolve common problems in concurrent programming, such as deadlocksTackle architecture challenges with design patternsWho this book is forThis book is for intermediate to experienced Python programmers who are looking to scale up their applications in a systematic and robust manner. Programmers from a range of backgrounds will find this book useful, including software engineers, scientific programmers, and software architects.
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Introduction to IoT with Machine Learning and Image Processing using Raspberry Pi
Machine Learning a branch of Artificial Intelligence is influencing the society, industry and academia at large. The adaptability of Python programming language to Machine Learning has increased its popularity further. Another technology on the horizon is Internet of Things (IoT). The present book tries to address IoT, Python and Machine Learning along with a small introduction to Image Processing. If you are a novice programmer or have just started exploring IoT or Machine Learning with Python, then this book is for you.Features: Raspberry Pi as IoT is described along with the procedure for installation and configuration.A simple introduction to Python Programming Language along with its popular library packages like NumPy, Pandas, SciPy and Matplotlib are dealt in an exhaustive manner along with relevant examples.Machine Learning along with Python Scikit-Learn library is explained to audience with an emphasis on supervised learning and classification.Image processing on IoT is introduced to the audience who love to apply Machine Learning algorithms to ImagesThe book follows hands-on approach and provide a huge collection of Python programs.
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Introduction to the Art of Programming Using Scala
With its flexibility for programming both small and large projects, Scala is an ideal language for teaching beginning programming. Yet there are no textbooks on Scala currently available for the CS1/CS2 levels. Introduction to the Art of Programming Using Scala presents many concepts from CS1 and CS2 using a modern, JVM-based language that works well for both programming in the small and programming in the large. The book progresses from true programming in the small to more significant projects later, leveraging the full benefits of object orientation. It first focuses on fundamental problem solving and programming in the small using the REPL and scripting environments. It covers basic logic and problem decomposition and explains how to use GUIs and graphics in programs. The text then illustrates the benefits of object-oriented design and presents a large collection of basic data structures showing different implementations of key ADTs along with more atypical data structures. It also introduces multithreading and networking to provide further motivating examples. By using Scala as the language for both CS1 and CS2 topics, this textbook gives students an easy entry into programming small projects as well as a firm foundation for taking on larger-scale projects. Many student and instructor resources are available at www.programmingusingscala.net
R 4,249.00
Introduction to Programming Using Processing, Second Edition
Written in an informal, conversational, and humorous style, the second edition of Introduction to Programming Using Processing makes learning programming a fun experience. The freely-available Processing language is ideal for a first course in programming. The simple-to-access graphics and multimedia capabilities of the language let students develop eye-catching, animated programs, instead of traditional programs that print text to the console. The text takes a "classes-later" approach, focusing on basics, using objects, selection, iteration, topdown design, and arrays, before writing classes. Every example is presented in the context of the RADIS (Requirements / Analyze / Design / Implement / Support) framework, with considerable attention paid to design. Other positive habits, like good commenting practice and coding style, are emphasized as well.
R 2,278.05
R 305.00
Python Programming for Mathematics
Python Programming for Mathematics focuses on the practical use of the Python language in a range of different areas of mathematics. Through fifty-five exercises of increasing difficulty, the book provides an expansive overview of the power of using programming to solve complex mathematical problems.This book is intended for undergraduate and graduate students who already have learned the basics of Python programming and would like to learn how to apply that programming skill in mathematics.FeaturesInnovative style that teaches programming skills via mathematical exercises.Ideal as a main textbook for Python for Mathematics courses, or as a supplementary resource for Numerical Analysis and Scientific Computing courses.
R 8,098.04
