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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
Python for Data Mining Quick Syntax Reference
Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis.Python for Data Mining Quick Syntax Reference covers each concept concisely, with many illustrative examples. You'll be introduced to several data mining packages, with examples of how to use each of them. The first part covers core Python including objects, lists, functions, modules, and error handling. The second part covers Python's most important data mining packages: NumPy and SciPy for mathematical functions and random data generation, pandas for dataframe management and data import, Matplotlib for drawing charts, and scikitlearn for machine learning. What You'll LearnInstall Python and choose a development environmentUnderstand the basic concepts of object-oriented programmingImport, open, and edit filesReview the differences between Python 2.x and 3.xWho This Book Is ForProgrammers new to Python's data mining packages or with experience in other languages, who want a quick guide to Pythonic tools and techniques.
R 752.00
Advanced Mathematics and Mechanics Applications Using MATLAB
Since its introduction in 1984, MATLAB's ever-growing popularity and functionality have secured its position as an industry-standard software package. The user-friendly, interactive environment of MATLAB 6.x, which includes a high-level programming language, versatile graphics capabilities, and abundance of intrinsic functions, helps users focus on their applications rather than on programming errors. MATLAB has now leapt far ahead of FORTRAN as the software of choice for engineering applications.
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R 414.94
Methods and Models in Mathematical Programming
This book focuses on mathematical modeling, describes the process of constructing and evaluating models, discusses the challenges and delicacies of the modeling process, and explicitly outlines the required rules and regulations so that the reader will be able to generalize and reuse concepts in other problems by relying on mathematical logic.Undergraduate and postgraduate students of different academic disciplines would find this book a suitable option preparing them for jobs and research fields requiring modeling techniques. Furthermore, this book can be used as a reference book for experts and practitioners requiring advanced skills of model building in their jobs.
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Mathematical Programming The State of the Art
In the late forties, Mathematical Programming became a scientific discipline in its own right. Since then it has experienced a tremendous growth. Beginning with economic and military applications, it is now among the most important fields of applied mathematics with extensive use in engineering, natural sciences, economics, and biological sciences. The lively activity in this area is demonstrated by the fact that as early as 1949 the first "Symposium on Mathe- matical Programming" took place in Chicago. Since then mathematical programmers from all over the world have gath- ered at the intfrnational symposia of the Mathematical Programming Society roughly every three years to present their recent research, to exchange ideas with their colleagues and to learn about the latest developments in their own and related fields. In 1982, the XI. International Symposium on Mathematical Programming was held at the University of Bonn, W. Germany, from August 23 to 27. It was organized by the Institut fUr Okonometrie und Operations Re- search of the University of Bonn in collaboration with the Sonderforschungs- bereich 21 of the Deutsche Forschungsgemeinschaft.This volume constitutes part of the outgrowth of this symposium and docu- ments its scientific activities. Part I of the book contains information about the symposium, welcoming addresses, lists of committees and sponsors and a brief review about the Ful- kerson Prize and the Dantzig Prize which were awarded during the opening ceremony.
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R 763.00
Numerical Mathematics
This book provides the mathematical foundations of numerical methods and demonstrates their performance on examples, exercises and real-life applications. This is done using the MATLAB software environment, which allows an easy implementation and testing of the algorithms for any specific class of problems. The book is addressed to students in Engineering, Mathematics, Physics and Computer Sciences. In the second edition of this extremely popular textbook on numerical analysis, the readability of pictures, tables and program headings has been improved. Several changes in the chapters on iterative methods and on polynomial approximation have also been
R 3,367.09
Python 3 Using DeepSeek
This book is your definitive guide to mastering DeepSeek, a leading open-source Large Language Model (LLM), and leveraging its power through practical Python programming. It is structured to build your expertise from foundational Python data structures and object-oriented programming to advanced model deployment.The initial chapters establish a strong technical base in Python's core features, including comprehensions, iterators, and the OOP paradigm. The focus then shifts entirely to DeepSeek, detailing its innovative Mixture-of-Experts (MoE) architecture, its superior performance on code-centric benchmarks like HumanEval, and its efficiency advantages. You will gain crucial insight into model management, specifically through the concept of quantization and local deployment with tools like Ollama, which is essential for maximizing performance while minimizing resource usage. The final chapter provides numerous, practical Python mini-projects, allowing you to immediately apply DeepSeek's capabilities to a range of real-world tasks from basic web scraping and data visualization to advanced object-oriented programming and linear regression.Python 3 Using DeepSeek is essential reading for Python developers (intermediate to advanced), machine learning practitioners, and data scientists. It is your guide to integrating high-performing, open-source LLMs into your workflows, particularly for code generation, algorithmic reasoning, and highly efficient local model deployment.
R 6,118.00
Floating Point Numerics for Games and Simulations
Floating point is ubiquitous in computers, where it is the default way to represent non-integer numbers. However, few people understand it. We all see weird behavior sometimes, and many programmers treat it as a mystical and imprecise system of math that just works until it sometimes doesn’t. We hear that we shouldn’t trust floating point with money, we know that 0.1 + 0.2 does not equal 0.3, and “NaN” shows up in our logs when things break. We rarely hear why any of this is the case, and less about what to do about it.This book pulls back the veil on floating point and shows how this number system we program with every day works. It discusses how to leverage the number system for common calculations, particularly in graphics and simulations, and avoid pitfalls. Further, we will review methods that can give you either better performance or better accuracy on tasks like numerical integration and function approximation, so you can learn to make the right tradeoffs in your programs.This book builds upon a basic knowledge of calculus and linear algebra, working with illustrative examples that demonstrate concepts rather than relying on theoretical proofs. Along the way, we will learn why Minecraft has struggled with boat physics and what the heck John Carmack was thinking with Quake III’s infamous fast reciprocal square root algorithm. By the end of the book, you will be able to understand how to work with floating point in a practical sense, from tracking down and preventing error in small calculations to choosing numerical building blocks for complex 3D simulations.Gives insight into how and why floating-point math worksDescribes how floating-point error arises and how to avoid itSurveys numerical methods important to graphics and numerical simulationsIncludes modern techniques to apply to your numerical problemsShows how to hack the floating-point numbers to compute faster and more accurately
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R 344.00
Applied Linear Regression for Business Analytics with Python
This textbook provides a practical, business-focused introduction to regression analysis using Python. It equips readers with the intuition, coding skills, and statistical tools needed to transform raw data into actionable insights. In today’s data-driven economy, where organizations rely on analytics for pricing, marketing, employee retention, and financial forecasting, regression remains a cornerstone method.The text bridges theory and application by combining clear explanations, step-by-step coding, and real-world business case studies. A distinguishing feature is the introduction of the Ravix package, a regression modeling and visualization framework developed to streamline regression workflows in Python. Ravix simplifies model building, produces clear and interpretable output, and integrates seamlessly with core scientific Python libraries such as NumPy, Pandas, Statsmodels, and Scikit-learn. By reducing coding complexity and emphasizing interpretation, Ravix makes modern regression techniques accessible to students, analysts, and professionals.
R 4,030.00
Practical Foundations of Mathematics
Practical Foundations collects the methods of construction of the objects of twentieth-century mathematics. Although it is mainly concerned with a framework essentially equivalent to intuitionistic Zermelo-Fraenkel logic, the book looks forward to more subtle bases in categorical type theory and the machine representation of mathematics. Each idea is illustrated by wide-ranging examples, and followed critically along its natural path, transcending disciplinary boundaries between universal algebra, type theory, category theory, set theory, sheaf theory, topology and programming. Students and teachers of computing, mathematics and philosophy will find this book both readable and of lasting value as a reference work.
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R 3,111.44
R 313.00
Visual Studio Code for Python Programmers
Become proficient and efficient with Visual Studio Code and learn how to integrate all your external tools! Visual Studio Code for Python Programmers helps Python developers become not just familiar, but productive in Visual Studio Code. To start, you’ll find the steps for installing Visual Studio Code on Windows, Mac and Linux platforms, along with an introduction to the editing features of the workspace. Coverage of more advanced functionality includes managing source code, debugging, unit testing, and Jupyter Notebook support. The book finishes with a walk-through of real-world projects which utilize Visual Studio Code features introduced in the book. For developers, the choice of an editor is a very personal one. You have idiosyncratic needs and wants that are unique to you as a developer. This book will help you learn how to customize Visual Studio Code to meet your needs and Python development workflow. Introduces you to the features of the Visual Studio Code workspace and how those features can be customizedDemonstrates how Visual Studio Code allows you to choose your structure according to your needsCovers editing code in Python, including syntax highlighting, code completion, object definition, refactoring, and code navigationDescribes Git integration and how to perform common Git functions (commits, checkouts, branches, and merges) from within Visual Studio CodeHighlights debugging features for Python developers A final section on Real World Applications will step you through several examples (and features integration with Django, Flask, Jupyter Notebook, Docker, and Azure), so you can hit the ground running with Visual Studio Code.
R 1,140.00
Python 3 Using DeepSeek
This book is your definitive guide to mastering DeepSeek, a leading open-source Large Language Model (LLM), and leveraging its power through practical Python programming. It is structured to build your expertise from foundational Python data structures and object-oriented programming to advanced model deployment.The initial chapters establish a strong technical base in Python's core features, including comprehensions, iterators, and the OOP paradigm. The focus then shifts entirely to DeepSeek, detailing its innovative Mixture-of-Experts (MoE) architecture, its superior performance on code-centric benchmarks like HumanEval, and its efficiency advantages. You will gain crucial insight into model management, specifically through the concept of quantization and local deployment with tools like Ollama, which is essential for maximizing performance while minimizing resource usage. The final chapter provides numerous, practical Python mini-projects, allowing you to immediately apply DeepSeek's capabilities to a range of real-world tasks from basic web scraping and data visualization to advanced object-oriented programming and linear regression.Python 3 Using DeepSeek is essential reading for Python developers (intermediate to advanced), machine learning practitioners, and data scientists. It is your guide to integrating high-performing, open-source LLMs into your workflows, particularly for code generation, algorithmic reasoning, and highly efficient local model deployment.
R 2,674.00
R 794.00
Python for Data Science For Dummies
Let Python do the heavy lifting for you as you analyze large datasets Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner’s guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge and insights. This new edition is updated for the latest version of Python and includes current, relevant data examples. Get a firm background in the basics of Python coding for data analysisLearn about data science careers you can pursue with Python coding skillsIntegrate data analysis with multimedia and graphics Manage and organize data with cloud-based relational databasesPython careers are on the rise. Grab this user-friendly Dummies guide and gain the programming skills you need to become a data pro.
R 835.00
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: .
R 1,163.84
Python for Information Professionals
Python for Information Professionals: How to Design Practical Applications to Capitalize on the Data Explosion is an introduction to the Python programming language for library and information professionals with little or no prior experience. As opposed to the many Python books available today that focus on the language only from a general sense, this book is designed specifically for information professionals who are seeking to advance their career prospects or challenge themselves in new ways by acquiring skills within the rapidly expanding field of data science. Readers of Python for Information Professionals will learn to:Develop Python applications for the retrieval, cleaning, and analysis of large datasets. Design applications to support traditional library functions and create new opportunities to maximize library value. Consider data security and privacy relevant to data analysis when using the Python language.
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