Search results for "Python Programming for Mathematics"
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R 1,219.00
Oxford Mathematics Primary Years Programme Student Book 3
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
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Multi-Platform Graphics Programming with Kivy
Modern science requires computer graphics models to provide realistic visual renderings. Learning the appropriate programming tools for 2D and 3D modeling doesn’t have to be so difficult. This book reviews the best programming tools to achieve this and explains how to apply them to mobile platforms like Android. Multi-Platform Graphics Programming with Kivy provides a straightforward introductory approach for designing 2D, 3D, and stereoscopic applications, using analytical equations from vector algebra. Throughout the book you’ll look closely at this approach and develop scenes in Kivy, taking advantage of powerful mathematical functions for arrays by NumPy for Python. Unbuntu is used to develop the programs, which allows you to easily convert to Android platform. Each chapter contains step-by-step descriptions on each subject and provides complete program listings.What You’ll LearnWork with Kivy, a modern, powerful multi-platform graphics systemConvert and run programs on Android devicesProgram, fill faces, and rotate 2D and 3D polygonsApply the concepts of 2D and 3D applicationsDevelop stereoscopic scenesReview a straightforward introduction to 2D, 3D, and stereoscopic graphics applicationsUse simple analytical equations from vector algebraWho This Book Is ForThe primary audience is students and researchers in graphics programming with experience in analytical equations.
R 1,254.00
Artificial Intelligence Programming with Python
A hands-on roadmap to using Python for artificial intelligence programming In Practical Artificial Intelligence Programming with Python: From Zero to Hero, veteran educator and photophysicist Dr. Perry Xiao delivers a thorough introduction to one of the most exciting areas of computer science in modern history. The book demystifies artificial intelligence and teaches readers its fundamentals from scratch in simple and plain language and with illustrative code examples. Divided into three parts, the author explains artificial intelligence generally, machine learning, and deep learning. It tackles a wide variety of useful topics, from classification and regression in machine learning to generative adversarial networks. He also includes: Fulsome introductions to MATLAB, Python, AI, machine learning, and deep learningExpansive discussions on supervised and unsupervised machine learning, as well as semi-supervised learningPractical AI and Python “cheat sheet” quick referencesThis hands-on AI programming guide is perfect for anyone with a basic knowledge of programming—including familiarity with variables, arrays, loops, if-else statements, and file input and output—who seeks to understand foundational concepts in AI and AI development.
R 958.00
Geocomputation with Python
Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python's capabilities for spatial data analysis, as well as dozens of worked-through examples covering the entire range of standard GIS operations. A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve. This book is an excellent starting point for those new to working with geographic data with Python, making it ideal for students and practitioners beginning their journey with Python.Key features:Showcases the integration of vector and raster datasets operations.Provides explanation of each line of code in the book to minimize surprises.Includes example datasets and meaningful operations to illustrate the applied nature of geographic research.Another unique feature is that this book is part of a wider community. Geocomputation with Python is a sister project of Geocomputation with R (Lovelace, Nowosad, and Muenchow 2019), a book on geographic data analysis, visualization, and modeling using the R programming language that has numerous contributors and an active community.The book teaches how to import, process, examine, transform, compute, and export spatial vector and raster datasets with Python, the most widely used language for data science and many other domains. Reading the book and running the reproducible code chunks within will make you a proficient user of key packages in the ecosystem, including shapely, geopandas, and rasterio. The book also demonstrates how to make use of dozens of additional packages for a wide range of tasks, from interactive map making to terrain modeling. Geocomputation with Python provides a firm foundation for more advanced topics, including spatial statistics, machine learning involving spatial data, and spatial network analysis, and a gateway into the vibrant and supportive community developing geographic tools in Python and beyond.
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R 458.00
Object-Oriented Approach to Problem Solving and Machine Learning with Python
This book is a comprehensive guide suitable for beginners and experienced developers alike. It teaches readers how to master object-oriented programming (OOP) with Python and use it in real-world applications.Start by solidifying your OOP foundation with clear explanations of core concepts such as use cases and class diagrams. This book goes beyond theory as you get practical examples with well-documented source code available in the book and on GitHub.This book doesn’t stop at the basics. Explore how OOP empowers fields such as data persistence, graphical user interfaces (GUIs), machine learning, and data science, including social media analysis. Learn about machine learning algorithms for classification, regression, and unsupervised learning, putting you at the forefront of AI innovation.Each chapter is designed for hands-on learning. You’ll solidify your understanding with case studies, exercises, and projects that apply your newfound knowledge to real-world scenarios. The progressive structure ensures mastery, with each chapter building on the previous one, reinforced by exercises and projects.Numerous code examples and access to the source code enhance your learning experience. This book is your one-stop shop for mastering OOP with Python and venturing into the exciting world of machine learning and data science.
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R 647.36
Python for Experimental Psychologists
Python for Experimental Psychologists equips researchers who have no prior programming experience with the essential knowledge to independently script experiments and analyses in the programming language Python. The book offers an excellent introduction, whether you are an undergraduate, a PhD candidate, or an established researcher.This updated edition is on Python 3 (the most current version). It starts by teaching the fundamentals of programming in Python, and then offers several chapters on scripting experiments (displaying stimuli, obtaining and logging user input, precision timing, etc.) using the popular PsychoPy package. The remainder of the book is dedicated to data analysis, and includes chapters on reading/writing to text files, time series, eye tracking, data visualisation, and statistics.Access to a companion website enriches the learning experience with colour figures, example stimuli, datasets, scripts, and a portable Windows installation of Python. The book assumes no prior knowledge, and its informal and accessible tone helps readers with backgrounds in experimental psychology and cognitive neuroscience to quickly understand Python. It serves as a useful resource not only for researchers in these fields, but also for lecturers instructing on methodology and data analysis.Python for Experimental Psychologists demystifies programming complexities, and empowers researchers to proficiently conduct experiments and to analyse their results.
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R 580.00
Python for Asset Management
The asset management industry is undergoing a paradigm shift toward automation, transparency, and data-driven decision-making. Traditional tools (Excel, Bloomberg) are being replaced by programmable, scalable solutions. Yet, most finance professionals lack accessible, practical training in applying Python to real portfolio problems.Python For Asset Management fills that gap. The book empowers non-programmers—portfolio managers, risk analysts, and students—to implement advanced models themselves. It responds to the growing demand for quantitative literacy in finance, especially in sustainable investing and smart beta strategies, areas of active research for both of the authors.Features31 hands-on Python exercises with real data and executable code.Complete GitHub repository (MIT License) with all scripts, data pipelines, and results.Step-by-step implementation of VaR (historical, parametric, Monte Carlo), bond immunization, and factor models.Real-world decision tools — e.g., build a bullet/barbell/ladder bond portfolio, run Brinson-Fachler attribution, or backtest smart beta vs. index.Immediate applicability — every exercise produces a deliverable (e.g., optimal weights, risk report, attribution table) ready for client meetings.Focus on practical asset management workflows, not just theory.
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R 1,159.00
Practical Programming, 3e
Classroom-tested by tens of thousands of students, this new edition of the bestselling intro to programming book is for anyone who wants to understand computer science. Learn about design, algorithms, testing, and debugging. Discover the fundamentals of programming with Python 3.6--a language that's used in millions of devices. Write programs to solve real-world problems, and come away with everything you need to produce quality code. This edition has been updated to use the new language features in Python 3.6. No programming experience required! Incremental examples show you the steps and missteps that happen while developing programs, so you know what to expect when you tackle a problem on your own. Inspired by "How to Design Programs" (HtDP), discover a five-step recipe for designing functions, which helps you learn the concepts--and becomes an integral part of writing programs. In this detailed introduction to Python and to computer programming, find out exactly what happens when your programs are executed. Work with numbers, text, big data sets, and files using real-world examples. Create and use your own data types. Make your programs reliable, work with databases, download data from the web automatically, and build user interfaces. As you use the fundamental programming tools in this book, you'll see how to document and organize your code so that you and other programmers can more easily read and understand it. This new edition takes advantage of Python 3.6's new features, including type annotations on parameters, return types and variable declarations, and changes to string formatting. Most importantly, you'll learn how to think like a professional programmer. What You Need: You'll need to download Python 3.6, available from https://python.org. With that download comes IDLE, the editor we use for writing and running Python programs. (If you use Linux, you may need to install Python 3.6 and IDLE separately.)
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Programming with Python
This book is an introduction to Python Programming and provides a practical approach to the subject. The basic concepts of Python are explained in detail and augmented with examples and diagrams for a thorough understanding of the subject.The book is primarily aimed at students with little or no prior knowledge of programming languages. However, self-taught and hobbyist programmers, scientists, engineers, computing professionals and computer scientists and others who need to program as part of their work may also use this book for understanding the basic concepts of Python.Print edition not for sale in South Asia (India, Sri Lanka, Nepal, Bangladesh, Pakistan or Bhutan)
R 3,008.83
Python Practice Lab
A guide to learning basic programming by writing fun, working programs that gradually become more complexThis classroom-tested, workbook-style text teaches basic programming by guiding readers to write Python programs that mimic interactive chatbots. Unlike textbooks with opaque examples explained in dry, monotonous code, Python Practice Lab engages readers immediately, with more than thirty motivating and hands-on examples. Readers learn by writing fun, working programs that gradually become more difficult as new concepts are introduced. Most exercises are open ended, promoting creativity in the process of learning. Along with coding practice, the book offers brief introductions to a range of other topics in computer science, including recommendation systems, computer vision, and big data, and relates these subjects to the programming concepts covered in the book. Python Practice Lab will be an essential resource for anyone who wants to learn to program, instructors teaching Python to beginners, and students who want to supplement their coursework by building complete and functional programs.Uses natural language and text strings rather than math as the main building blocks for learning about program structureRewrites code comprehension exercises in equivalent code with inclusive and approachable variables rather than terse, single-letter variablesChallenges readers to write a full program in each chapterPresents a selection of projects at the end of the book that integrates the concepts introduced in previous chapters
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R 454.00
Programming with Python for Social Scientists
As data become ′big′, fast and complex, the software and computing tools needed to manage and analyse them are rapidly developing. Social scientists need new tools to meet these challenges, tackle big datasets, while also developing a more nuanced understanding of - and control over - how these computing tools and algorithms are implemented. Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge. It guides you through the full research process, from question to publication, including:the fundamentals of why and how to do your own programming in social scientific research,questions of ethics and research design,a clear, easy to follow ′how-to′ guide to using Python, with a wide array of applications such as data visualisation, social media data research, social network analysis, and more.Accompanied by numerous code examples, screenshots, sample data sources, this is the textbook for social scientists looking for a complete introduction to programming with Python and incorporating it into their research design and analysis.
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Grundlagen der Python-Programmierung
Dieses Buch vermittelt einen systematischen Einstieg in die Python-Programmierung und führt Schritt für Schritt durch alle wichtigen Grundlagen bis hin zu fortgeschrittenen Konzepten. Es beginnt mit den zentralen Sprachelementen wie Datentypen, Variablen, Operatoren, Zeichenketten und numerischen Funktionen und zeigt anhand klarer Beispiele, wie Python effizient eingesetzt wird.Aufbauend darauf behandelt das Buch strukturierte Daten wie Listen, Tupel, Dictionaries und Sets sowie Kontrollstrukturen mit Verzweigungen und Schleifen. Im weiteren Verlauf werden Funktionen, Fehlerbehandlung und objektorientierte Programmierung ausführlich erklärt. Ein eigenes Kapitel widmet sich dem Arbeiten mit Dateien, inklusive Lesen, Schreiben, CSV-Verarbeitung und grundlegenden Funktionen des Betriebssystems.Abgerundet wird das Werk durch einen großen Übungsteil mit praxisnahen Aufgaben und vollständigen Lösungen, die das eigenständige Lernen unterstützen und den Stoff festigen. Damit eignet sich das Buch sowohl für Einsteigerinnen und Einsteiger in Informatik und Data Science als auch für Anwenderinnen und Anwender, die ein solides Fundament für weiterführende Python-Anwendungen aufbauen möchten.
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R 519.00
Pragmatic Python Programming
Explore the world of programming languages through Python and learn the building blocks of writing programs. This book covers Python 3.10, explaining it through six key concepts. Each chapter contains a real-world example with practical advice and a section on advanced concepts. You'll start by reviewing the concept of expressions and functions, which are two of the core building blocks of programming languages. You'll then move on to object-oriented concepts to help gain a practical understanding of Python, along with a chapter on control flow constructs. The book also takes a close look at sequences, explaining constructs and additional types, and wraps up with a chapter on modules, focusing on how to use and create packages. Whether you’re new to programming or already an experienced developer, upon finishing this book, you will have a solid understanding of Python's state-of-the-art development features.What You Will LearnStudy the six main concepts of the programming languagesLearn how to use programming language constructs through examplesReview the core Python language notations and concepts.Start using Python as a working languageWho This Book Is ForSoftware developers wanting to gain professional core Python knowledge quickly, and non-developers wanting to gain an understanding of programming concepts.
R 1,026.00
