Search results for "python programming for mathematics"
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R 1,161.00
Practical Numerical Mathematics With Matlab: A Workbook
This workbook and solutions manual is intended for advanced undergraduate or beginning graduate students as a supplement to a traditional course in numerical mathematics and as preparation for independent research involving numerical mathematics. The solutions manual provides complete MATLAB code and numerical results for each of the exercises in the workbook and will be especially useful for those students without previous MATLAB programming experience. It is also valuable for classroom instructors to help pinpoint the author's intent in each exercise and to provide a model for graders. Upon completion of this material, students will have a working knowledge of MATLAB programming, they will have themselves programmed algorithms encountered in classwork and textbooks, and they will know how to check and verify their own programs against hand calculations and by reference to theoretical results, special polynomial solutions and other specialized solutions. No previous programming experience with MATLAB is necessary.
R 2,737.14
R 458.00
R 1,191.00
Linear Algebra for Data Science with Python
Linear Algebra for Data Science with Python provides an introduction to vectors and matrices within the context of data science. This book starts from the fundamentals of vectors and how vectors are used to model data, builds up to matrices and their operations, and then considers applications of matrices and vectors to data fitting, transforming time-series data into the frequency domain, and dimensionality reduction. This book uses a computational-first approach: the reader will learn how to use Python and the associated data-science libraries to work with and visualize vectors and matrices and their operations, as well as to import data to apply these techniques. Readers learn the basics of performing vector and matrix operations by hand but are also shown how to use several different Python libraries for performing these operations.Key Features:Teaches the most important concepts and techniques for working with multi-dimensional data using vectors and matrices.Introduces readers to some of the most important Python libraries for working with data, including NumPy and PyTorch.Demonstrate the application of linear algebra in real data and engineering applications.Includes many color visualizations to illustrate mathematical operations involving vectors and matrices.Provides practice and feedback through a unique set of online, interactive tools on the accompanying website.
R 4,066.00
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 2,172.44
Python for Secret Agents
If you are a Python beginner who is looking to learn the language through interesting projects, this book is for you. A basic knowledge of programming and statistics is beneficial to get the most out of the book.
R 1,010.00
R 420.00
Applied Mathematics: Body and Soul
Applied Mathematics: Body & Soul is a mathematics education reform project developed at Chalmers University of Technology and includes a series of volumes and software. The program is motivated by the computer revolution opening new possibilities of computational mathematical modeling in mathematics, science and engineering. It consists of a synthesis of Mathematical Analysis (Soul), Numerical Computation (Body) and Application. Volumes I-III present a modern version of Calculus and Linear Algebra, including constructive/numerical techniques and applications intended for undergraduate programs in engineering and science. Further volumes present topics such as Dynamical Systems, Fluid Dynamics, Solid Mechanics and Electro-Magnetics on an advanced undergraduate/graduate level. The authors are leading researchers in Computational Mathematics who have written various successful books.
R 1,573.11
R 550.00
R 641.00
Introduction to Programming Concepts with Case Studies in Python
The current text provides a clear introduction to Computer Science concepts in a programming environment. It is designed as suitable use in freshman- or introductory level coursework in CS and provides the fundamental concepts as well as abstract theorems for solving computational problems. The Python language serves as a medium for illustrating and demonstrating the concepts.
R 1,649.00
Exercises in Programming Style
The first edition of Exercises in Programming Style was honored as an ACM Notable Book and praised as "The best programming book of the decade." This new edition retains the same presentation but has been upgraded to Python 3, and there is a new section on neural network styles.Using a simple computational task (term frequency) to illustrate different programming styles, Exercises in Programming Style helps readers understand the various ways of writing programs and designing systems. It is designed to be used in conjunction with code provided on an online repository. The book complements and explains the raw code in a way that is accessible to anyone who regularly practices the art of programming. The book can also be used in advanced programming courses in computer science and software engineering programs.The book contains 40 different styles for writing the term frequency task. The styles are grouped into ten categories: historical, basic, function composition, objects and object interactions, reflection and metaprogramming, adversity, data-centric, concurrency, interactivity, and neural networks. The author states the constraints in each style and explains the example programs. Each chapter first presents the constraints of the style, next shows an example program, and then gives a detailed explanation of the code. Most chapters also have sections focusing on the use of the style in systems design as well as sections describing the historical context in which the programming style emerged.
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R 611.00
R 4,488.40
R 336.00
Quick Functional Programming
Why learn functional programming? Isn’t that some complicated ivory-tower technique used only in obscure languages like Haskell?In fact, functional programming is actually very simple. It’s also very powerful, as Haskell demonstrates by throwing away all the conventional programming tools and using only functional programming features. But it doesn’t have to be done that way.Functional programming is a power tool that you can use in addition to all your usual tools, to whatever extent your current mainstream language supports it. Most languages have at least basic support.In this book we use Python and Java and, as a bonus, Scala. If you prefer another language, there will be minor differences in syntax, but the concepts are the same.Give functional programming a try. You may be surprised how much a single power tool can help you in your day-to-day programming.
R 5,620.40
Exercises in Programming Style
The first edition of Exercises in Programming Style was honored as an ACM Notable Book and praised as "The best programming book of the decade." This new edition retains the same presentation but has been upgraded to Python 3, and there is a new section on neural network styles.Using a simple computational task (term frequency) to illustrate different programming styles, Exercises in Programming Style helps readers understand the various ways of writing programs and designing systems. It is designed to be used in conjunction with code provided on an online repository. The book complements and explains the raw code in a way that is accessible to anyone who regularly practices the art of programming. The book can also be used in advanced programming courses in computer science and software engineering programs.The book contains 40 different styles for writing the term frequency task. The styles are grouped into ten categories: historical, basic, function composition, objects and object interactions, reflection and metaprogramming, adversity, data-centric, concurrency, interactivity, and neural networks. The author states the constraints in each style and explains the example programs. Each chapter first presents the constraints of the style, next shows an example program, and then gives a detailed explanation of the code. Most chapters also have sections focusing on the use of the style in systems design as well as sections describing the historical context in which the programming style emerged.
R 2,297.02
R 550.00
Data Structures for Engineers and Scientists Using Python
The text covers the fundamentals of Python programming and the implementation of data structures using Python programming with the help of worked-out examples. It provides a learning tool for engineers as well as for researchers and scientists of advanced level. The text further discusses important concepts such as polynomial manipulation, sparse matrices, implementation of stack using queue model, and topological sorting.This book:Discusses the implementation of various data structures such as an array, stack, queue, tree, and graph along with sorting and searching algorithms. Includes programming tips to highlight important concepts and help readers avoid common programming errors. Presents each concept of data structure with a different approach and implements the same using Python programming. Offers rich chapter-end pedagogy including objective-type questions (with answers), review questions, and programming exercises to facilitate revision. Covers fundamentals of Python up to object-oriented concepts including regular expression. It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
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R 268.00
R 641.00
R 1,010.00
R 763.00
Oxford Mathematics Primary Years Programme Practice and Mastery Book 3
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
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 1,573.11
Elementary Number Theory with Programming
A highly successful presentation of the fundamental concepts of number theory and computer programming Bridging an existing gap between mathematics and programming, Elementary Number Theory with Programming provides a unique introduction to elementary number theory with fundamental coverage of computer programming. Written by highly-qualified experts in the fields of computer science and mathematics, the book features accessible coverage for readers with various levels of experience and explores number theory in the context of programming without relying on advanced prerequisite knowledge and concepts in either area. Elementary Number Theory with Programming features comprehensive coverage of the methodology and applications of the most well-known theorems, problems, and concepts in number theory. Using standard mathematical applications within the programming field, the book presents modular arithmetic and prime decomposition, which are the basis of the public-private key system of cryptography. In addition, the book includes: Numerous examples, exercises, and research challenges in each chapter to encourage readers to work through the discussed concepts and ideasSelect solutions to the chapter exercises in an appendixPlentiful sample computer programs to aid comprehension of the presented material for readers who have either never done any programming or need to improve their existing skill setA related website with links to select exercisesAn Instructor’s Solutions Manual available on a companion website Elementary Number Theory with Programming is a useful textbook for undergraduate and graduate-level students majoring in mathematics or computer science, as well as an excellent supplement for teachers and students who would like to better understand and appreciate number theory and computer programming. The book is also an ideal reference for computer scientists, programmers, and researchers interested in the mathematical applications of programming.
R 2,912.00
R 641.00
R 1,131.98
R 550.00
R 641.00
Game Programming with Code Angel
Program in Python on a Raspberry Pi or PC by developing six computer games. Each game project is split into several chapters of the book. Rather than taking you through programming techniques as standalone concepts, this book explains concepts as they are used within a game.You'll learn about variables; integer, real, Boolean and string data types; conditional if statements; fixed loops and conditional loops; modularity; arrays and lists; and predefined functions. You’ll also discover the PyGame library, which is popularly used in the development of 2D games.Key programming concepts are revisited in subsequent projects in the book to consolidate prior learning. Beyond teaching you how to code, this book explains the programming logic behind each project—exemplifying the process of designing and writing a computer game.All the projects in this book are supported by Code Angel (mycodeangel.com). Code Angel Code Angel largely serves students and new developers and the projects work by encouraging you to ‘Learn…then play’. Taking this approach, you'll be able to build fun 2D games and enjoy playing them by yourself or with friends. Developing games in this way keeps you engaged, gives a purpose as you work through each project, and offers a sense of achievement when each game is finished.What You'll Learn Integrate the fundamentals of the Python 3 programming languageProgram fun, classic computer games you can then playDevelop computational thinking skills and abilities that can be applied to other venturesWho This Book Is ForStudents, hobbyists, new developers or anyone wishing to learn how to design and write computer games.
R 1,254.00
