Search results for "introduction to python programming"
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R 1,046.88
R 409.00
Functional Python Programming
Python isn't all about object-oriented programming. Discover a valuable way of thinking about code design through a function-first approach – and learn when you need to use it. Now with detailed exercises at the end of every chapter!Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesLearn how, when, and why to adopt functional elements in your projectsExplore the Python modules essential to functional programming, like itertools and functoolsRevised to cover new features of Python 3.10, exercises at the end of every chapter, and moreBook DescriptionNot enough developers understand the benefits of functional programming, or even what it is. Author Steven Lott demystifies the approach, teaching you how to improve the way you code in Python and make gains in memory use and performance. Starting from the fundamentals, this book shows you how to apply functional thinking and techniques in a range of scenarios, with examples centered around data cleaning and exploratory data analysis. You'll learn how to use generator expressions, list comprehensions, and decorators to your advantage. You don't have to abandon object-oriented design completely, though – you'll also see how Python's native object-orientation is used in conjunction with functional programming techniques. By the end of this book, you'll be well versed in the essential functional programming features of Python, and understand why and when functional thinking helps. You'll also have all the tools you need to pursue any additional functional topics that are not part of the Python language.What you will learnUse Python's libraries to avoid the complexities of state-changing classesLeverage built-in higher-order functions to avoid rewriting common algorithmsWrite generator functions to create lazy processingDesign and implement decorators for functional compositionMake use of Python type annotations to describe parameters and results of functionsApply functional programming to concurrency and web servicesExplore the PyMonad library for stateful simulationsWho this book is forThe functional paradigm is very useful for programmers working in data science, but any Python developer who wants to create more reliable, succinct, and expressive code will have much to learn from this book.No prior knowledge of functional programming is required to get started, though Python programming knowledge is assumed. A running Python environment is essential.
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R 550.00
R 4,559.00
Introduction to Modeling and Simulation with MATLAB® and Python
Introduction to Modeling and Simulation with MATLAB and Python is intended for students and professionals in science, social science, and engineering that wish to learn the principles of computer modeling, as well as basic programming skills. The book content focuses on meeting a set of basic modeling and simulation competencies that were developed as part of several National Science Foundation grants. Even though computer science students are much more expert programmers, they are not often given the opportunity to see how those skills are being applied to solve complex science and engineering problems and may also not be aware of the libraries used by scientists to create those models.The book interleaves chapters on modeling concepts and related exercises with programming concepts and exercises. The authors start with an introduction to modeling and its importance to current practices in the sciences and engineering. They introduce each of the programming environments and the syntax used to represent variables and compute mathematical equations and functions. As students gain more programming expertise, the authors return to modeling concepts, providing starting code for a variety of exercises where students add additional code to solve the problem and provide an analysis of the outcomes. In this way, the book builds both modeling and programming expertise with a "just-in-time" approach so that by the end of the book, students can take on relatively simple modeling example on their own.Each chapter is supplemented with references to additional reading, tutorials, and exercises that guide students to additional help and allows them to practice both their programming and analytical modeling skills. In addition, each of the programming related chapters is divided into two parts – one for MATLAB and one for Python. In these chapters, the authors also refer to additional online tutorials that students can use if they are having difficulty with any of the topics.The book culminates with a set of final project exercise suggestions that incorporate both the modeling and programming skills provided in the rest of the volume. Those projects could be undertaken by individuals or small groups of students.The companion website at http://www.intromodeling.com provides updates to instructions when there are substantial changes in software versions, as well as electronic copies of exercises and the related code. The website also offers a space where people can suggest additional projects they are willing to share as well as comments on the existing projects and exercises throughout the book. Solutions and lecture notes will also be available for qualifying instructors.
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R 487.00
R 811.23
Introduction to Data Systems
Encompassing a broad range of forms and sources of data, this textbook introduces data systems through a progressive presentation. Introduction to Data Systems covers data acquisition starting with local files, then progresses to data acquired from relational databases, from REST APIs and through web scraping. It teaches data forms/formats from tidy data to relationally defined sets of tables to hierarchical structure like XML and JSON using data models to convey the structure, operations, and constraints of each data form.The starting point of the book is a foundation in Python programming found in introductory computer science classes or short courses on the language, and so does not require prerequisites of data structures, algorithms, or other courses. This makes the material accessible to students early in their educational career and equips them with understanding and skills that can be applied in computer science, data science/data analytics, and information technology programs as well as for internships and research experiences. This book is accessible to a wide variety of students. By drawing together content normally spread across upper level computer science courses, it offers a single source providing the essentials for data science practitioners. In our increasingly data-centric world, students from all domains will benefit from the “data-aptitude” built by the material in this book.
R 2,015.00
Introduction to IoT with Machine Learning and Image Processing using Raspberry Pi
Machine Learning a branch of Artificial Intelligence is influencing the society, industry and academia at large. The adaptability of Python programming language to Machine Learning has increased its popularity further. Another technology on the horizon is Internet of Things (IoT). The present book tries to address IoT, Python and Machine Learning along with a small introduction to Image Processing. If you are a novice programmer or have just started exploring IoT or Machine Learning with Python, then this book is for you.Features: Raspberry Pi as IoT is described along with the procedure for installation and configuration.A simple introduction to Python Programming Language along with its popular library packages like NumPy, Pandas, SciPy and Matplotlib are dealt in an exhaustive manner along with relevant examples.Machine Learning along with Python Scikit-Learn library is explained to audience with an emphasis on supervised learning and classification.Image processing on IoT is introduced to the audience who love to apply Machine Learning algorithms to ImagesThe book follows hands-on approach and provide a huge collection of Python programs.
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R 965.00
R 397.00
Expert Python Programming
Refine your Python programming skills and build professional grade applications with this comprehensive guideKey FeaturesCreate manageable code that can run in various environments with different sets of dependenciesImplement effective Python data structures and algorithms to write optimized codeDiscover the exciting new features of Python 3.7Book DescriptionPython is a dynamic programming language that's used in a wide range of domains thanks to its simple yet powerful nature. Although writing Python code is easy, making it readable, reusable, and easy to maintain is challenging. Complete with best practices, useful tools, and standards implemented by professional Python developers, the third edition of Expert Python Programming will help you overcome this challenge.The book will start by taking you through the new features in Python 3.7. You'll then learn the advanced components of Python syntax, in addition to understanding how to apply concepts of various programming paradigms, including object-oriented programming, functional programming, and event-driven programming. This book will also guide you through learning the best naming practices, writing your own distributable Python packages, and getting up to speed with automated ways of deploying your software on remote servers. You’ll discover how to create useful Python extensions with C, C++, Cython, and CFFI. Furthermore, studying about code management tools, writing clear documentation, and exploring test-driven development will help you write clean code.By the end of the book, you will have become an expert in writing efficient and maintainable Python code.What you will learnExplore modern ways of setting up repeatable and consistent development environmentsPackage Python code effectively for community and production useLearn modern syntax elements of Python programming such as f-strings, enums, and lambda functionsDemystify metaprogramming in Python with metaclassesWrite concurrent code in PythonExtend Python with code written in different languagesIntegrate Python with code written in different languagesWho this book is forThis book will appeal to you if you’re a programmer looking to take your Python knowledge to the next level by writing efficient code and learning the latest features of version 3.7 and above.
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R 611.00
R 556.97
Introduction to Programming with Fortran
This fourth Edition presents new examples on submodules, derived type i/o, object oriented programming, abstract interfaces and procedure pointers, C interop, sorting and searching, statistics and converting to more modern versions of Fortran.Key FeaturesHighlights the core language features of modern Fortran including data typing, array processing, control structures, functions, subroutines, modules and submodules, user defined types, pointers, operator overloading, generic programming, parallel programming, abstract interfaces, procedure pointersPinpoints common problems that occur when programmingIllustrates the use of several compilersIntroduction to Programming with Fortran has been written for the complete beginner with little or no programming background as well as existing Fortran programmers and those with programming experience in other languages
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Introduction to Numerical Methods for Variational Problems
This textbook teaches finite element methods from a computational point of view. It focuses on how to develop flexible computer programs with Python, a programming language in which a combination of symbolic and numerical tools is used to achieve an explicit and practical derivation of finite element algorithms. The finite element library FEniCS is used throughout the book, but the content is provided in sufficient detail to ensure that students with less mathematical background or mixed programming-language experience will equally benefit. All program examples are available on the Internet.
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Mastering GUI Programming with Python
An advanced guide to creating powerful high-performance GUIs for modern, media-rich applications in various domains such as business and game developmentKey FeaturesGain comprehensive knowledge of Python GUI development using PyQt 5.12Explore advanced topics including multithreaded programming, 3D animation, and SQL databasesBuild cross-platform GUIs for Windows, macOS, Linux, and Raspberry PiBook DescriptionPyQt5 has long been the most powerful and comprehensive GUI framework available for Python, yet there is a lack of cohesive resources available for Python programmers to learn how to use it. This book will be your comprehensive guide to exploring GUI development with PyQt5. You will get started with an introduction to PyQt5, before going on to develop stunning GUIs with modern features. You will learn how to build forms using QWidgets and delve into important aspects of GUI development such as layouts, size policies, and event-driven programming. Moving ahead, you’ll discover PyQt5’s most powerful features through chapters on audio-visual programming with QtMultimedia, database-driven software with QtSQL, and web browsing with QtWebEngine. Next, in-depth coverage of multithreading and asynchronous programming will help you run tasks asynchronously and build high-concurrency processes with ease. In later chapters, you’ll gain insights into QOpenGLWidget, along with mastering techniques for creating 2D graphics with QPainter. You’ll also explore PyQt on a Raspberry Pi and interface it with remote systems using QtNetwork. Finally, you will learn how to distribute your applications using setuptools and PyInstaller. By the end of this book, you will have the skills you need to develop robust GUI applications using PyQt.What you will learnGet to grips with the inner workings of PyQt5Understand how elements in a GUI application communicate with signals and slotsStudy techniques for styling an applicationExplore database-driven applications with the QtSQL moduleCreate 2D graphics with QPainterDelve into 3D graphics with QOpenGLWidgetBuild network and web-aware applications with QtNetwork and QtWebEngineWho this book is forThis book is for programmers who want to create attractive, functional, and powerful GUIs using the Python language. You’ll also find this book useful if you are a student, professional, or anyone who wants to start exploring GUIs. Although prior knowledge of the Python language is assumed, experience with PyQt, Qt, or GUI programming is not required.
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R 794.00
R 531.00
Introduction to the Tools of Scientific Computing
The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike standard approaches, it does not focus on any specific language, but aims to explain the underlying ideas.Typically, new concepts are first introduced in the particularly user-friendly Python language and then transferred and extended in various programming environments from C/C++, Julia and MATLAB to Maple and Mathematica. This includes various approaches to distributed computing. By examining and comparing different languages, the book is also helpful for mathematicians and practitioners in deciding which programming language to use for which purposes.At a more advanced level, special tools for the automated solution of partial differential equations using the finite element method are discussed. On a more experimental level, the basic methods of scientific machine learning in artificial neural networks are explained and illustrated.
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Programming Microcontrollers with Python
For the first time microcontrollers are powerful enough to be programmed in Python. The landscape of embedded systems development is changing, microcontrollers are becoming more powerful, and the rise of the internet of things is leading more developers to get into hardware. This book provides the solid foundation to start your journey of embedded systems development and microcontroller programming with Python. You’ll quickly realize the value of using Python. The theme of the book is simplicity and the cleanness and elegance of Python makes that possible. Featuring a step-by-step approach, this single source guide balances complexity and clarity with insightful explanations that you’ll easily grasp. Python is quickly becoming the language of choice for applications such as machine learning and computer vision on embedded devices. What would previously be daunting and exceedingly difficult to do in C or C++ is now possible with Python because of its level of abstraction. Programming Microcontrollers with Python is your path to bringing your existing skills to the embedded space. What You’ll LearnReview microcontroller basics and the hardware and software requirements Understand an embedded system’s general architectureFollow the steps needed to carry a product to market Take a crash course in Python programming Program a microcontrollerInterface with a microcontroller using LCD and Circuit PythonUse and control sensorsWho This Book Is ForThose getting started with microcontrollers, those new to C, C++, and Arduino programming, web developers looking to get into IoT, or Python programmers who wish to control hardware devices.
R 1,254.00
Introduction to Statistics with Python
Now in its second edition, this textbook provides an introduction to Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics.For this new edition, the introductory chapters on Python, data input and visualization have been reworked and updated. The chapter on experimental design has been expanded, and programs for the determination of confidence intervals commonly used in quality control have been introduced. The book also features a new chapter on finding patterns in data, including time series. A new appendix describes useful programming tools, such as testing tools, code repositories, and GUIs.The provided working code for Python solutions, together with easy-to-follow examples, will reinforce the reader’s immediate understanding of the topic. Accompanying data sets and Python programs are also available online. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis.With examples drawn mainly from the life and medical sciences, this book is intended primarily for masters and PhD students. As it provides the required statistics background, the book can also be used by anyone who wants to perform a statistical data analysis.
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R 762.00
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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