Search results for "python programming for mathematics"
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R 1,191.00
Mathematics, Physics & Chemistry With The Wolfram Language
The Wolfram language is the programming language of Mathematica, used increasingly by scientists due to its ease of learning and user-friendliness. This book focuses on applications of the Wolfram language to applied mathematics, physics and chemistry. Topics discussed are broad and comprehensive, from differential equations and special functions to fractals and chess, from electromagnetism and optics to relativity and black holes. There is also extensive coverage of quantum theory and quantum chemistry, and the book is peppered with more than 200 color graphics to aid visualization of these concepts. The program codes are provided online as Mathematica notebooks, allowing readers to modify them and manipulate the graphics in real time. This book should be a valuable resource for researchers, educators and students in science and computing who can profit from a more interactive form of instruction.
R 5,422.00
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 4,831.20
R 641.00
R 214.00
Introduction to Programming with Mathematica®
Accompanying the book, as with all TELOS sponsored publications, is an electronic component. In this case it is a DOS-Diskette produced by one of the coauthors, Paul Wellin. This diskette consists of Mathematica notebooks and packages which contain the codes for all examples and exercises in the book, as well as additional materials intended to extend many ideas covered in the text. It is of great value to teachers, students, and others using this book to learn how to effectively program with Mathematica .
R 1,624.83
Head First Programming
Looking for a reliable way to learn how to program on your own, without being overwhelmed by confusing concepts? "Head First Programming" introduces the core concepts of writing computer programs - variables, decisions, loops, functions, and objects - which apply regardless of the programming language. This book offers concrete examples and exercises in the dynamic and versatile Python language to demonstrate and reinforce these concepts. You can learn the basic tools to start writing the programs that interest you, and get a better understanding of what software can (and cannot) do. When you're finished, you'll have the necessary foundation to learn any programming language or tackle any software project you choose.With a focus on programming concepts, this book teaches you how to: understand the core features of all programming languages, including variables, statements, decisions, loops, expressions, and operators; reuse code with functions; use library code to save time and effort; select the best data structure to manage complex data; write programs that talk to the Web; share your data with other programs; and, write programs that test themselves and help you avoid embarrassing coding errors. We think your time is too valuable to waste struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, "Head First Programming" uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.
R 1,368.00
R 1,283.00
Julia 1.0 Programming Complete Reference Guide
Learn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the webKey FeaturesLeverage Julia's high speed and efficiency to build fast, efficient applicationsPerform supervised and unsupervised machine learning and time series analysisTackle problems concurrently and in a distributed environmentBook DescriptionJulia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI).You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs.Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system.By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications.This Learning Path includes content from the following Packt products:Julia 1.0 Programming - Second Edition by Ivo BalbaertJulia Programming Projects by Adrian SalceanuWhat you will learnCreate your own types to extend the built-in type systemVisualize your data in Julia with plotting packagesExplore the use of built-in macros for testing and debuggingIntegrate Julia with other languages such as C, Python, and MATLABAnalyze and manipulate datasets using Julia and DataFramesDevelop and run a web app using Julia and the HTTP packageBuild a recommendation system using supervised machine learningWho this book is forIf you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. Basic knowledge of mathematics and programming is a must.
R 2,170.02
Python For ArcGIS
This book introduces Python scripting for geographic information science (GIS) workflow optimization using ArcGIS. It builds essential programming skills for automating GIS analysis. Over 200 sample Python scripts and 175 classroom-tested exercises reinforce the learning objectives. Readers will learn to: • Write and run Python in the ArcGIS Python Window, the PythonWin IDE, and the PyScripter IDE • Work with Python syntax and data types • Call ArcToolbox tools, batch process GIS datasets, and manipulate map documents using the arcpy package • Read and modify proprietary and ASCII text GIS data • Parse HTML web pages and KML datasets • Create Web pages and fetch GIS data from Web sources. • Build user-interfaces with the native Python file dialog toolkit or the ArcGIS Script tools and PyToolboxes Python for ArcGIS is designed as a primary textbook for advanced-level students in GIS. Researchers, government specialists and professionals working in GIS will also find this book useful as a reference.
R 3,347.70
Modelling in Mathematical Programming
This book provides basic tools for learning how to model in mathematical programming, from models without much complexity to complex system models. It presents a unique methodology for the building of an integral mathematical model, as well as new techniques that help build under own criteria. It allows readers to structure models from the elements and variables to the constraints, a basic modelling guide for any system with a new scheme of variables, a classification of constraints and also a set of rules to model specifications stated as logical propositions, helping to better understand models already existing in the literature. It also presents the modelling of all possible objectives that may arise in optimization problems regarding the variables values.The book is structured to guide the reader in an orderly manner, learning of the components that the methodology establishes in an optimization problem. The system includes the elements, which are all the actors that participate in the system, decision activities that occur in the system, calculations based on the decision activities, specifications such as regulations, impositions or actions of defined value and objective criterion, which guides the resolution of the system.
R 4,211.60
R 428.00
Non-Programmers Tutorial For Python 2 and 3
This book is a tutorial for the Python 2 and 3 programming language designed for someone with no programming experience. All the examples work in Python 2.6 and Python 3.
R 414.02
R 1,568.42
Text Analysis in Python for Social Scientists
Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it.
R 865.00
Mathematics for the Liberal Arts
Presents a clear bridge between mathematics and the liberal arts Mathematics for the Liberal Arts provides a comprehensible and precise introduction to modern mathematics intertwined with the history of mathematical discoveries. The book discusses mathematical ideas in the context of the unfolding story of human thought and highlights the application of mathematics in everyday life. Divided into two parts, Mathematics for the Liberal Arts first traces the history of mathematics from the ancient world to the Middle Ages, then moves on to the Renaissance and finishes with the development of modern mathematics. In the second part, the book explores major topics of calculus and number theory, including problem-solving techniques and real-world applications. This book emphasizes learning through doing, presents a practical approach, and features: A detailed explanation of why mathematical principles are true and how the mathematical processes workNumerous figures and diagrams as well as hundreds of worked examples and exercises, aiding readers to further visualize the presented conceptsVarious real-world practical applications of mathematics, including error-correcting codes and the space shuttle programVignette biographies of renowned mathematiciansAppendices with solutions to selected exercises and suggestions for further reading Mathematics for the Liberal Arts is an excellent introduction to the history and concepts of mathematics for undergraduate liberal arts students and readers in non-scientific fields wishing to gain a better understanding of mathematics and mathematical problem-solving skills.
R 3,412.00
Thinking About Programs
This book describes how to think about computer programs, and how to use mathematics as part of that thinking. Many books and online tutorials teach the basics of coding: the syntax of the language, and how to translate an algorithm into code. But how do you come up with that algorithm? And how can you be confident that the algorithm is correct?The first part of the book considers small programs that use a loop, and how to demonstrate their correctness using loop invariants. It also covers some algorithms and algorithmic techniques that every programmer should know. The second half of the book considers slightly larger programs. It teaches the basics of modularisation, splitting up a program into manageable chunks. It teaches about abstract datatypes, values within a program that can be treated as mathematical values: how to specify their behaviours formally; and how to treat them as abstract mathematical objects when programming. It also teaches how to use data structures to represent abstract datatypes, and what it means for such a representation to be correct. And it presents some abstract datatypes and data structures that every programmer should know.The book is aimed at those who want to obtain a better understanding of programs they work on, and so become better programmers. The target audience ranges from those who are just starting out, to professional programmers. The book aims to be pragmatic: the philosophy is to include enough formality to be convincing and to guide the programmer towards correct code, without getting bogged down in the mathematics.
R 1,953.00
Thinking About Programs
This book describes how to think about computer programs, and how to use mathematics as part of that thinking. Many books and online tutorials teach the basics of coding: the syntax of the language, and how to translate an algorithm into code. But how do you come up with that algorithm? And how can you be confident that the algorithm is correct?The first part of the book considers small programs that use a loop, and how to demonstrate their correctness using loop invariants. It also covers some algorithms and algorithmic techniques that every programmer should know. The second half of the book considers slightly larger programs. It teaches the basics of modularisation, splitting up a program into manageable chunks. It teaches about abstract datatypes, values within a program that can be treated as mathematical values: how to specify their behaviours formally; and how to treat them as abstract mathematical objects when programming. It also teaches how to use data structures to represent abstract datatypes, and what it means for such a representation to be correct. And it presents some abstract datatypes and data structures that every programmer should know.The book is aimed at those who want to obtain a better understanding of programs they work on, and so become better programmers. The target audience ranges from those who are just starting out, to professional programmers. The book aims to be pragmatic: the philosophy is to include enough formality to be convincing and to guide the programmer towards correct code, without getting bogged down in the mathematics.
R 2,604.00
Student's Guide to the Study, Practice, and Tools of Modern Mathematics
A Student’s Guide to the Study, Practice, and Tools of Modern Mathematics provides an accessible introduction to the world of mathematics. It offers tips on how to study and write mathematics as well as how to use various mathematical tools, from LaTeX and Beamer to Mathematica® and Maple™ to MATLAB® and R. Along with a color insert, the text includes exercises and challenges to stimulate creativity and improve problem solving abilities.The first section of the book covers issues pertaining to studying mathematics. The authors explain how to write mathematical proofs and papers, how to perform mathematical research, and how to give mathematical presentations.The second section focuses on the use of mathematical tools for mathematical typesetting, generating data, finding patterns, and much more. The text describes how to compose a LaTeX file, give a presentation using Beamer, create mathematical diagrams, use computer algebra systems, and display ideas on a web page. The authors cover both popular commercial software programs and free and open source software, such as Linux and R.Showing how to use technology to understand mathematics, this guide supports students on their way to becoming professional mathematicians. For beginning mathematics students, it helps them study for tests and write papers. As time progresses, the book aids them in performing advanced activities, such as computer programming, typesetting, and research.
R 2,815.03
R 519.00
Connecting Discrete Mathematics and Computer Science
Computer science majors taking a non-programming-based course like discrete mathematics might ask 'Why do I need to learn this?' Written with these students in mind, this text introduces the mathematical foundations of computer science by providing a comprehensive treatment of standard technical topics while simultaneously illustrating some of the broad-ranging applications of that material throughout the field. Chapters on core topics from discrete structures – like logic, proofs, number theory, counting, probability, graphs – are augmented with around 60 'computer science connections' pages introducing their applications: for example, game trees (logic), triangulation of scenes in computer graphics (induction), the Enigma machine (counting), algorithmic bias (relations), differential privacy (probability), and paired kidney transplants (graphs). Pedagogical features include 'Why You Might Care' sections, quick-reference chapter guides and key terms and results summaries, problem-solving and writing tips, 'Taking it Further' asides with more technical details, and around 1700 exercises, 435 worked examples, and 480 figures.
R 3,133.00
R 1,130.00
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R 764.00
R 641.00
R 1,015.19
Oxford Mathematics Primary Years Programme Student Book 2
Build mathematical knowledge and skills and explore the PYP transdisciplinary themes via this colourful, inquiry-based Student Book.· Fully support the PYP approach with comprehensive coverage of the PYP Mathematics Scope and Sequence· Progressively build understanding via guided, independent and extended learning activities· Cover the five strands of Number, Pattern and Function, Measurement, Shape and Space, and Data Handling using the PYP methodology of constructing, transferring and applying meaning· Encourage learners to explore and apply knowledge using real-world problems
R 1,001.00
R 1,328.09
R 305.00
R 671.00
R 764.00
Computer-Based Mathematics Education and the Use of MatCos Software in Primary and Secondary Schools
The theme of inserting new digital technologies into the teaching and learning of mathematics from primary and secondary schools has provoked a wide and interesting debate. One such debate is the reformation of the foundations of mathematics to include computation (what and how to calculate) among the traditional themes (Arithmetic, Geometry, etc.) of mathematics. Thus, the authors propose the MatCos Project as a new approach for solving this issue. Computer-Based Mathematics Education and the Use of MatCos Software in Primary and Secondary Schools is a critical reference source that proposes a new pedagogical-learning paradigm that guides students in the formation of an active, logical-sequential, intuitive, and creative thinking that directs them towards problem-solving and starts students with computational thinking and programming in a natural way. The content of the book is divided into two parts, with the first exploring theoretical and pedagogical notes on mathematics and the second examining the MatCos programming environment and its systematic inclusion in teaching practice. Highlighting themes that include computer-assisted instruction, teaching-learning sequences, and programming, this book is ideal for in-service teachers, mathematics instructors, academicians, researchers, and students.
R 8,376.84
Python Artificial Intelligence Projects for Beginners
Build smart applications by implementing real-world artificial intelligence projectsKey FeaturesExplore a variety of AI projects with PythonGet well-versed with different types of neural networks and popular deep learning algorithmsLeverage popular Python deep learning libraries for your AI projectsBook DescriptionArtificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence.This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library.By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progressWhat you will learnBuild a prediction model using decision trees and random forestUse neural networks, decision trees, and random forests for classificationDetect YouTube comment spam with a bag-of-words and random forestsIdentify handwritten mathematical symbols with convolutional neural networksRevise the bird species identifier to use imagesLearn to detect positive and negative sentiment in user reviewsWho this book is forPython Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you’re able to play around with code
R 912.00
Discrete Mathematics
Computing developed as a branch of mathematics, only to drift away from this home as computer science diverged towards more general topics such as the theory of how a computer works. Recently the emphasis has become more mathematical and the new disciplines of software engineering and information technology have emerged. This book is designed to form the basis of a one year course in discrete mathematics for first year computer scientists or software engineers. The material presented covers much of undergraduate algebra with a particular bias towards the computing applications. Topics covered include mathematical logic, set theory, finite and infinite relations and mappings, graphs, graphical algorithms and axiom systems. It concludes with implementations of many of the algorithms in Modula-2 to illustrate how the mathematics may be turned into concrete calculations. Numerous examples and exercises are included with selected solutions to the problems appearing in the appendix. Discrete mathematics is the basic language which every student of computing should take pride in mastering and this book should prove an essential tool in this aim.
R 2,845.80
Introduction to Python for Humanists
This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming language, and as it presumes no knowledge on the part of the reader about computers or coding concepts allows the reader to gradually learn the more complex tasks that are currently popular in the field of digital humanities. This book will be aimed at undergraduates, graduates, and faculty who are interested in learning how to use Python as a tool within their workflow. An Introduction to Python for Digital Humanists will act as a primer for students who wish to use Python, allowing them to engage with more advanced textbooks. This book fills a real need, as it is first Python introduction to be aimed squarely at humanities students, as other books currently available do not approach Python from a humanities perspective. It will be designed so that those experienced in Python can teach from it, in addition to allowing those who are interested in being self-taught can use it for that purpose.Key Features: Data analysis Data science Computational humanities Digital humanities Python Natural language processing Social network analysisApp development
R 2,528.00
R 428.00
Python for Bioinformatics
In today's data driven biology, programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language.This new edition is updated throughout to Python 3 and is designed not just to help scientists master the basics, but to do more in less time and in a reproducible way. New developments added in this edition include NoSQL databases, the Anaconda Python distribution, graphical libraries like Bokeh, and the use of Github for collaborative development.
R 4,524.65
