Search results for "python arithmetic"
Items we need to order for you
R 1,219.00
Python for Engineers and Scientists
This book equips technical professionals with a complete, structured path to mastering Python for real-world engineering and scientific applications. As Python becomes central to research labs, automation, simulation, and data-driven engineering, the learning curve remains steep. This book bridges that gap with a practical roadmap from fundamentals to professional-grade scientific computing.The book begins by building a strong programming foundation—covering Python’s architecture, essential syntax, data structures, modules, functions, control flow, and object-oriented design. Readers learn not only how to write Python, but why the language behaves the way it does, ensuring deep understanding and strong problem-solving skills. From there, the focus shifts to practical engineering tools. Dedicated chapters train readers in file handling, math modules, and key scientific libraries including NumPy, SciPy, Pandas, and Matplotlib, enabling efficient computation, signal processing, data analysis, and high-quality visualization. Advanced chapters then showcase Python’s versatility through GUI development with Kivy, database work with SQLAlchemy, and hands-on control system modeling and analysis. Each topic is rooted in industry and academic scenarios, making the content directly applicable to automation, simulation, data workflows, and engineering computation.Whether you're a student building foundational skills or a professional modernizing engineering workflows, this guide provides the programming depth, scientific tools, and applied knowledge needed to use Python confidently for prototyping, simulation, analysis, and automation. It is the one-stop resource for mastering Python in technical disciplines.What you will learn:Learn core Python programming concepts, including variables, loops, functions, and object-oriented principles in a scientific and engineering context.Build strong skills in key scientific Python libraries such as NumPy, Pandas, Matplotlib, and SciPy for computation, analysis, and visualization.Apply Python to real-world engineering scenarios, including dynamic control systems and automation workflows.Develop interactive engineering applications by creating graphical user interfaces (GUIs) with Kivy. Who this book is for:This book is intended for practicing engineers and scientists across various disciplines of engineering who need to use Python for complex problem-solving, simulation, and data analysis in their work.
R 1,368.00
R 633.00
R 855.35
R 367.00
R 618.00
R 585.00
R 565.00
Computational Intelligence-based Optimization Algorithms
Computational intelligence-based optimization methods, also known as metaheuristic optimization algorithms, are a popular topic in mathematical programming.These methods have bridged the gap between various approaches and created a new school of thought to solve real-world optimization problems. In this book, we have selected some of the most effective and renowned algorithms in the literature. These algorithms are not only practical but also provide thought-provoking theoretical ideas to help readers understand how they solve optimization problems. Each chapter includes a brief review of the algorithm’s background and the fields it has been used in.Additionally, Python code is provided for all algorithms at the end of each chapter, making this book a valuable resource for beginner and intermediate programmers looking to understand these algorithms.
R 3,041.00
Computer Arithmetic in Practice
Computer Arithmetic in Practice - Exercises and Programming is a simple, brief introductory volume for undergraduate and graduate students at university courses interested in understanding the foundation of computers. It is focused on numeric data formats and capabilities of computer to perform basic arithmetic operations. It discusses mainly such topics as: Basic concepts of computer architecture Assembly language programming skills Data formats used to express integer and real numbers Algorithms of basic arithmetic operations Short overview of nonlinear functions evaluation Discussion on limited number representation and computer arithmetic Exercises and programming tasks.This book provides an accessible overview of common data formats used to write numbers in programming languages and how the computer performs four basic arithmetic operations from the point of view of the processor instruction set. The book is primarily didactic in nature, therefore the theoretical information is enriched with many numerical examples and exercises to be solved using a "sheet of paper and a pencil". Answers are provided for most of the tasks. The theoretical discussed issues are illustrated by listings of algorithms presenting the way hot to implement arithmetic operations in low level language. taking. It allows to develop the skills of optimal programming taking into considerations the computer architecture and limitations. Creating software using low level language programming, despite the initial difficulties, gives the ability to control the code and create efficient applications. This allows for effective consolidation of knowledge and acquisition of practical skills, required at the stage of education, mainly a specialist in the field of information technology, electronics, telecommunications, other related disciplines, or at the level of general education with introduction to information technology. It may be also useful for engineers interested in their own professional development and teachers as well.Sławomir Gryś is a university professor at Częstochowa University of Technology, Poland. He has conducted many courses focused on analog electronics, logical devices, foundations of computer architecture and organization, low-level programming techniques in assembly and C languages for embedded systems, image processing and recognition. He is the author or co-author of several scientific monographs, book chapters, academic textbook, patent and more than 60 papers in journals and domestic and international conference proceedings in Poland, Germany, Canada and Australia.
R 7,566.46
Mathematical Methods in Data Science
Bridge the gap between theoretical concepts and their practical applications with this rigorous introduction to the mathematics underpinning data science. It covers essential topics in linear algebra, calculus and optimization, and probability and statistics, demonstrating their relevance in the context of data analysis. Key application topics include clustering, regression, classification, dimensionality reduction, network analysis, and neural networks. What sets this text apart is its focus on hands-on learning. Each chapter combines mathematical insights with practical examples, using Python to implement algorithms and solve problems. Self-assessment quizzes, warm-up exercises and theoretical problems foster both mathematical understanding and computational skills. Designed for advanced undergraduate students and beginning graduate students, this textbook serves as both an invitation to data science for mathematics majors and as a deeper excursion into mathematics for data science students.
R 2,707.00
R 1,326.18
R 3,660.00
Python Crash Course, 3rd Edition
Since its initial debut in 2015, this critically acclaimed quick-start guide to programming has taught millions of people all over the world to write clean code, solve problems, and build custom applications in the popular language of Python. The highly anticipated third edition of Python Crash Course has been completely revised with updated code, practices, and projects-making it the ultimate launchpad for beginners to start their engines and code in Python 3!
R 1,484.00
R 813.00
R 260.00
R 813.00
Python
Python's simplicity and versatility make it an ideal language for both beginners and experienced programmers. Its syntax facilitates a smooth learning curve, enabling individuals to concentrate on grasping programming concepts instead of wrestling with intricate syntax rules. The extensive standard library reinforces its practicality, offering pre-built modules and functions that reduce manual coding efforts. Python's versatility is evident in its applications, spanning web development, data analysis, machine learning, and automation. The language's interactive nature supports real-time code experimentation, stepping up the learning process and enhancing understanding. Python's wealth of online resources further enriches the learning experience, fostering a community where individuals can develop their programming skills. The book, "Python - A Practical Learning Approach," exemplifies Python's simplicity and versatility with numerous examples, ensuring a seamless learning journey. Beyond theory, the language's practicality allows learners to actively apply their knowledge in real-world scenarios, establishing Python as an asset in education.
R 7,559.12
R 813.00
R 716.00
R 1,333.68
R 463.56
R 587.00
R 690.52
R 1,252.38
Programming for Computations - Python
This book is published open access under a CC BY 4.0 license. This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.
R 2,198.00
Python Scripting for Computational Science
With a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language. All the tools and examples in this book are open source codes. This third edition features lots of new material. It is also released after a comprehensive reorganization of the text. The author has inserted improved examples and tools and updated information, as well as correcting any errors that crept in to the first imprint.
R 2,172.77
Subsystems of Second Order Arithmetic
Almost all of the problems studied in this book are motivated by an overriding foundational question: What are the appropriate axioms for mathematics? Through a series of case studies, these axioms are examined to prove particular theorems in core mathematical areas such as algebra, analysis, and topology, focusing on the language of second-order arithmetic, the weakest language rich enough to express and develop the bulk of mathematics. In many cases, if a mathematical theorem is proved from appropriately weak set existence axioms, then the axioms will be logically equivalent to the theorem. Furthermore, only a few specific set existence axioms arise repeatedly in this context, which in turn correspond to classical foundational programs. This is the theme of reverse mathematics, which dominates the first half of the book. The second part focuses on models of these and other subsystems of second-order arithmetic.
R 7,320.56
R 618.00
R 846.09
R 456.82
Conversations on Arithmetic
In this 1835 work, Sarah Porter, née Ricardo (1790–1862) shows her enthusiasm for arithmetic, and her concern for teaching it in a way that will develop the pupil's mind: 'There is no branch of early education so admirably adapted to call forth and strengthen the reasoning powers.' She uses the device of a conversation between pupil and teacher, popularised by Jane Marcet (several of whose works are reissued in the Cambridge Library Collection), to guide young Edmund from the written symbols for numbers through addition, subtraction, multiplication and division, fractions and decimals, proportion, and square and cube roots. Answers to the questions are provided at the end of the book. A member of the Central Society of Education, which promoted imaginative theories of education instead of rote learning, Mrs Porter reworked her book in 1852 as Rational Arithmetic, a more conventional and less entertaining textbook for use in schools.
R 1,435.07
R 1,041.00
Introduction to Python Programming and Data Structures, Global Edition
For introductory courses in Python Programming and Data Structures. A fundamentals first approach to programming helps students create efficient, elegant code. Introduction to Python Programming and Data Structures introduces students to basic programming concepts using a fundamentals-first approach that prepares students to learn object-oriented programming and advanced Python programming. This approach presents programming concepts and techniques that include control statements, loops, functions, and arrays before designing custom classes. Students learn basic logic and programming concepts prior to moving into object-oriented and GUI programming. The content incorporates a wide variety of problems with various levels of difficulty and covers many application areas to engage and motivate students.
R 3,391.00
Introduction to Computational Models with Python
Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy modules. The Python source code and data files are available on the author’s website.The book’s five sections present: An overview of problem solving and simple Python programs, introducing the basic models and techniques for designing and implementing problem solutions, independent of software and hardware toolsProgramming principles with the Python programming language, covering basic programming concepts, data definitions, programming structures with flowcharts and pseudo-code, solving problems, and algorithmsPython lists, arrays, basic data structures, object orientation, linked lists, recursion, and running programs under LinuxImplementation of computational models with Python using Numpy, with examples and case studies The modeling of linear optimization problems, from problem formulation to implementation of computational modelsThis book introduces the principles of computational modeling as well as the approaches of multi- and interdisciplinary computing to beginners in the field. It provides the foundation for more advanced studies in scientific computing, including parallel computing using MPI, grid computing, and other methods and techniques used in high-performance computing.
R 6,704.27
![Progressive Arithmetic [microform]](http://exclusivebooks.co.za/cdn/shop/products/9781014502919_c3edafd1-0f02-4963-bd33-bf84285f78f4.jpg?height=645&pad_color=fff&v=1707370735&width=315)
