Search results for "Handbook of Computer Programming with Python"
Items we need to order for you
Learn Robotics Programming
Develop an extendable smart robot capable of performing a complex series of actions with Python and Raspberry PiKey FeaturesGet up to speed with the fundamentals of robotic programming and build intelligent robotsLearn how to program a voice agent to control and interact with your robot's behaviorEnable your robot to see its environment and avoid barriers using sensorsBook DescriptionWe live in an age where the most complex or repetitive tasks are automated. Smart robots have the potential to revolutionize how we perform all kinds of tasks with high accuracy and efficiency. With this second edition of Learn Robotics Programming, you'll see how a combination of the Raspberry Pi and Python can be a great starting point for robot programming. The book starts by introducing you to the basic structure of a robot and shows you how to design, build, and program it. As you make your way through the book, you'll add different outputs and sensors, learn robot building skills, and write code to add autonomous behavior using sensors and a camera. You'll also be able to upgrade your robot with Wi-Fi connectivity to control it using a smartphone. Finally, you'll understand how you can apply the skills that you've learned to visualize, lay out, build, and code your future robot building projects. By the end of this book, you'll have built an interesting robot that can perform basic artificial intelligence operations and be well versed in programming robots and creating complex robotics projects using what you've learned.What you will learnLeverage the features of the Raspberry Pi OSDiscover how to configure a Raspberry Pi to build an AI-enabled robotInterface motors and sensors with a Raspberry PiCode your robot to develop engaging and intelligent robot behaviorExplore AI behavior such as speech recognition and visual processingFind out how you can control AI robots with a mobile phone over Wi-FiUnderstand how to choose the right parts and assemble your robotWho this book is forThis second edition of Learn Robotics Programming is for programmers, developers, and robotics enthusiasts who want to develop a fully functional robot and leverage AI to build interactive robots. Basic knowledge of the Python programming language will help you understand the concepts covered in this robot programming book more effectively.
R 2,279.00
Computer Programming in C for Beginners
This textbook is an ideal introduction in college courses or self-study for learning computer programming using the C language. Written for those with minimal or no programming experience, Computer Programming in C for Beginners offers a heavily guided, hands-on approach that enables the reader to quickly start programming, and then progresses to cover the major concepts of C programming that are critical for an early stage programmer to know and understand. While the progression of topics is conventional, their treatment is innovative and designed for rapid understanding of the many concepts in C that have traditionally proven difficult for beginners, such as variable typing and scope, function definition, passing by value, pointers, passing by reference, arrays, structures, basic memory management, dynamic memory allocation, and linked lists, as well as an introductory treatment of searching and sorting algorithms. Written in an informal but clear narrative, the book uses extensive examples throughout and provides detailed guidance on how to write the C code to achieve the objectives of the example problems. Derived from the author’s many years of teaching hands-on college courses, it encourages the reader to follow along by programming the progressively more complex exercise programs presented. In some sections, errors are purposely inserted into the code to teach the reader about the common pitfalls of programming in general, and the C language in particular.
R 2,569.80
Introduction to Quantitative Social Science with Python
Departing from traditional methodologies of teaching data analysis, this book presents a dual-track learning experience, with both Executive and Technical Tracks, designed to accommodate readers with various learning goals or skill levels. Through integrated content, readers can explore fundamental concepts in data analysis while gaining hands-on experience with Python programming, ensuring a holistic understanding of theory and practical application in Python.Emphasizing the practical relevance of data analysis in today's world, the book equips readers with essential skills for success in the field. By advocating for the use of Python, an open-source and versatile programming language, we break down financial barriers and empower a diverse range of learners to access the tools they need to excel.Whether you're a novice seeking to grasp the foundational concepts of data analysis or a seasoned professional looking to enhance your programming skills, this book offers a comprehensive and accessible guide to mastering the art and science of data analysis in social science research.Key Features:Dual-track learning: Offers both Executive and Technical Tracks, catering to readers with varying levels of conceptual and technical proficiency in data analysis.Includes comprehensive quantitative methodologies for quantitative social science studies.Seamless integration: Interconnects key concepts between tracks, ensuring a smooth transition from theory to practical implementation for a comprehensive learning experience.Emphasis on Python: Focuses on Python programming language, leveraging its accessibility, versatility, and extensive online support to equip readers with valuable data analysis skills applicable across diverse domains.
R 9,328.33
Thermal Physics Tutorials with Python Simulations
This book provides an accessible introduction to thermal physics with computational approaches that complement the traditional mathematical treatments of classical thermodynamics and statistical mechanics. It guides readers through visualizations and simulations in the Python programming language, helping them to develop their own technical computing skills (including numerical and symbolic calculations, optimizations, recursive operations, and visualizations). Python is a highly readable and practical programming language, making this book appropriate for students without extensive programming experience.This book may serve as a thermal physics textbook for a semester-long undergraduate thermal physics course or may be used as a tutorial on scientific computing with focused examples from thermal physics. This book will also appeal to engineering students studying intermediate-level thermodynamics as well as computer science students looking to understand how to apply their computer programming skills to science.Key features Major concepts in thermal physics are introduced cohesively through computational and mathematical treatments. Computational examples in Python programming language guide students on how to simulate and visualize thermodynamic principles and processes for themselves.
R 2,791.02
R 336.00
R 580.00
Artificial Intelligence with Python
Entering the field of artificial intelligence and data science can seem daunting to beginners with little to no prior background, especially those with no programming experience. The concepts used in self-driving cars and virtual assistants like Amazon’s Alexa may seem very complex and difficult to grasp. The aim of Artificial Intelligence in Python is to make AI accessible and easy to understand for people with little to no programming experience though practical exercises. Newcomers will gain the necessary knowledge on how to create such systems, which are capable of executing tasks that require some form of human-like intelligence.This book introduces readers to various topics and examples of programming in Python, as well as key concepts in artificial intelligence. Python programming skills will be imparted as we go along. Concepts and code snippets will be covered in a step-by-step manner, to guide and instill confidence in beginners. Complex subjects in deep learning and machine learning will be broken down into easy-to-digest content and examples. Artificial intelligence implementations will also be shared, allowing beginners to generate their own artificial intelligence algorithms for reinforcement learning, style transfer, chatbots, speech, and natural language processing.
R 2,015.00
R 611.00
R 305.00
AI Agents and Applications
Your AI prototype works once, then breaks. Ready for production stability? Tired of hallucinations ruining demos and stakeholder trust? Need agent workflows that survive real-world edge cases? Wondering how early adopters ship multi-agent systems today? Stop guessing, start delivering value with proven, open-source tools. Build confident, future-proof AI products your users will rely on. Prompt and context engineering: Produce accurate, hallucination-free outputs your business can trust. Advanced RAG techniques: Summarize documents, power semantic search, and answer questions with verifiable sources. LangGraph agent workflows: Orchestrate multi-step processes for complex, real-world tasks. MCP tool integration: Plug, compose, and reuse capabilities across projects for faster releases. End-to-end code examples: Copy, adapt, and deploy without time-consuming trial and error. AI Agents and Applications with LangChain, LangGraph, and MCP by seasoned developer Roberto Infante delivers a pragmatic, code-first roadmap in a clear softcover format. Infante shows exactly how to move from idea to production-grade AI. Each chapter builds a working solution, starting with solid prompt engineering, layering in advanced RAG, then evolving into structured agents and multi-agent systems. Visual explanations, annotated Python listings, and architecture diagrams speed learning and reduce guesswork. By the final page you will confidently design, test, and deploy LLM applications that delight users and impress stakeholders. The tools and patterns scale with your data, your team, and tomorrow’s models. Ideal for Python developers who grasp LLM basics and crave real production wins. Perfect for engineers, data scientists, and tech leads modernizing products with generative AI.
R 1,921.00
R 1,436.47
Python 3 Text Processing with NLTK 3 Cookbook
This book is intended for Python programmers interested in learning how to do natural language processing. Maybe you've learned the limits of regular expressions the hard way, or you've realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basic text processing concepts is expected. Some experience with regular expressions will also be helpful.
R 1,661.00
R 580.00
Introduction to Modern Scientific Programming and Numerical Methods
The ability to use computers to solve mathematical relationships is a fundamental skill for anyone planning a career in science or engineering. For this reason, numerical analysis is part of the core curriculum for just about every undergraduate physics and engineering department. But for most physics and engineering students, practical programming is a self-taught process.This book introduces the reader not only to the mathematical foundation but also to the programming paradigms encountered in modern hybrid software-hardware scientific computing. After completing the text, the reader will be well-versed in the use of different numerical techniques, programming languages, and hardware architectures, and will be able to select the appropriate software and hardware tool for their analysis.It can serve as a textbook for undergraduate courses on numerical analysis and scientific computing courses within engineering and physical sciences departments. It will also be a valuable guidebook for researchers with experimental backgrounds interested in working with numerical simulations, or for any new personnel working in scientific computing or data analysis.Key Features:• Includes examples of solving numerical problems in multiple programming languages, including MATLAB, Python, Fortran, C++, Arduino, Javascript, and Verilog.• Provides an introduction to modern high-performance computing technologies including multithreading, distributed computing, GPUs, microcontrollers, FPGAs, and web "cloud computing".• Contains an overview of numerical techniques not found in other introductory texts including particle methods, finite volume and finite element methods, Vlasov solvers, and molecular dynamics.Companions websites for this book can be accessed at https://plasmasimulationsbyexample.com/ and https://www.scientificprogrammingbook.com/.Lubos Brieda holds a Ph.D. in Aerospace and Mechanical Aerospace Engineering from the George Washington University in Washington, D.C., USA and an M.Sc. in Aerospace and Ocean Engineering from Virginia Tech in Blacksburg, VA, USA. He is the president of Particle in Cell Consulting, LLC, Westlake Village, CA, USA, while also serving as a part-time lecturer in the Department of Astronautical Engineering at University of Southern California, Los Angeles, CA. Dr. Brieda is the author of numerous simulation codes utilized by the aerospace and plasma modeling communities. Additionally, he maintains an online blog found at particleincell.com/blog focusing on scientific computing and since 2014 he has been teaching online courses on plasma simulations through his website.Joseph Wang is a Professor of Astronautics and Aerospace and Mechanical Engineering at the University of Southern California. Prof. Wang received his Ph.D in Aeronautics and Astronautics from Massachusetts Institute of Technology in 1991. Prof. Wang conducts research in computational physics, space technology, and space and planetary science. He and his students have
R 4,487.79
R 898.81
R 1,282.00
Programming Google App Engine 2e
As a cloud computing service, Google App Engine does more than provide access to a large system of servers. It also offers you a simple model for building applications that scale automatically to accommodate millions of users. With this updated edition of Programming Google App Engine, you'll get expert practical guidance that will help you make the best use of this powerful platform. Google engineer Dan Sanderson shows you how to design your applications for scalability, including ways to perform common development tasks using App Engine's APIs and scalable services. You'll learn about App Engine's application server architecture, runtime environments, and scalable datastore for distributing data, as well as techniques for optimizing your application. App Engine offers nearly unlimited computing power, and this book provides clear and concise instructions for getting the most from it right from the source. It's ideal for intermediate and advanced web developers familiar with Java or Python.*Discover the differences between traditional web development and development with App Engine * Learn the details of App Engine's Python and Java runtime environments * Understand how App Engine handles web requests and executes application code * Learn how to use App Engine's scalable datastore, including queries and indexes, transactions, and data modeling * Use task queues to parallelize and distribute work across the infrastructure * Deploy and manage applications with ease
R 1,730.00
R 1,131.20
Data Science and Analytics with Python
Since the first edition of “Data Science and Analytics with Python” we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business practitioners, but also by universities as a key textbook. In response to this growth, this new edition builds upon the success of its predecessor, expanding several sections, updating the code to reflect the latest advancements in Python libraries and modules, and addressing the ever-evolving landscape of generative AI (GenAI).This updated edition ensures that the examples and exercises remain relevant by incorporating the latest features of popular libraries such as Scikit-learn, pandas, and Numpy. Additionally, new sections delve into cutting-edge topics like generative AI, reflecting the advancements and the expanding role these technologies play. This edition also addresses crucial issues of explainability, transparency, and fairness in AI. These topics have rightly gained significant attention in recent years. As AI integrates more deeply into various aspects of our lives, understanding and mitigating biases, ensuring fairness, and maintaining transparency become paramount. This book provides comprehensive coverage of these topics, offering practical insights and guidance for data scientists and analysts.Designed as a practical companion for data analysts and budding data scientists, this book assumes a working knowledge of programming and statistical modelling but aims to guide readers deeper into the wonders of data analytics and machine learning. Maintaining the book's structure, each chapter stands alone as much as possible, allowing readers to use it as a reference as well as a textbook. Whether revisiting fundamental concepts or diving into new, advanced topics, this book offers something valuable for every reader.
R 3,171.08
Introduction to Programming with C++ for Engineers
A complete textbook and reference for engineers to learn the fundamentals of computer programming with modern C++ Introduction to Programming with C++ for Engineers is an original presentation teaching the fundamentals of computer programming and modern C++ to engineers and engineering students. Professor Cyganek, a highly regarded expert in his field, walks users through basics of data structures and algorithms with the help of a core subset of C++ and the Standard Library, progressing to the object-oriented domain and advanced C++ features, computer arithmetic, memory management and essentials of parallel programming, showing with real world examples how to complete tasks. He also guides users through the software development process, good programming practices, not shunning from explaining low-level features and the programming tools. Being a textbook, with the summarizing tables and diagrams the book becomes a highly useful reference for C++ programmers at all levels. Introduction to Programming with C++ for Engineers teaches how to program by: Guiding users from simple techniques with modern C++ and the Standard Library, to more advanced object-oriented design methods and language featuresProviding meaningful examples that facilitate understanding of the programming techniques and the C++ language constructionsFostering good programming practices which create better professional programmersMinimizing text descriptions, opting instead for comprehensive figures, tables, diagrams, and other explanatory materialGranting access to a complementary website that contains example code and useful links to resources that further improve the reader’s coding abilityIncluding test and exam question for the reader’s review at the end of each chapter Engineering students, students of other sciences who rely on computer programming, and professionals in various fields will find this book invaluable when learning to program with C++.
R 3,177.00
R 1,301.00
Internet of Things with Python
Interact with the world and rapidly prototype IoT applications using PythonAbout This Book• Rapidly prototype even complex IoT applications with Python and put them to practical use• Enhance your IoT skills with the most up-to-date applicability in the field of wearable tech, smart environments, and home automation• Interact with hardware, sensors, and actuators and control your DIY IoT projects through PythonWho This Book Is ForThe book is ideal for Python developers who want to explore the tools in the Python ecosystem in order to build their own IoT applications and work on IoT-related projects. It is also a very useful resource for developers with experience in other programming languages that want to easily prototype IoT applications with the Intel Galileo Gen 2 board.What You Will Learn• Prototype and develop IoT solutions from scratch with Python as the programming language• Develop IoT projects with Intel Galileo Gen 2 board along with Python• Work with the different components included in the boards using Python and the MRAA library• Interact with sensors, actuators, and shields• Work with UART and local storage• Interact with any electronic device that supports the I2C bus• Allow mobile devices to interact with the board• Work with real-time IoT and cloud services• Understand Big Data and IoT analyticsIn DetailInternet of Things (IoT) is revolutionizing the way devices/things interact with each other. And when you have IoT with Python on your side, you'll be able to build interactive objects and design them.This book lets you stay at the forefront of cutting-edge research on IoT. We'll open up the possibilities using tools that enable you to interact with the world, such as Intel Galileo Gen 2, sensors, and other hardware. You will learn how to read, write, and convert digital values to generate analog output by programming Pulse Width Modulation (PWM) in Python. You will get familiar with the complex communication system included in the board, so you can interact with any shield, actuator, or sensor.Later on, you will not only see how to work with data received from the sensors, but also perform actions by sending them to a specific shield. You'll be able to connect your IoT device to the entire world, by integrating WiFi, Bluetooth, and Internet settings. With everything ready, you will see how to work in real time on your IoT device using the MQTT protocol in python.By the end of the book, you will be able to develop IoT prototypes with Python, libraries, and tools.Style and approach This book takes a tutorial-like approach with mission critical chapters. The initial chapters are introductions that set the premise for useful examples covered in later chapters.
R 1,889.00
How Computer Programming Works
This unique book uses full color illustrations to help readers understand the principles behind all computer programming. It is the book for beginners to read before they start learning computer programming. It offers non-programmers a basis for understanding what programmers do. The author Daniel Appleman is well-known for his bestselling books on VB.
R 684.00
Practical Maya Programming with Python
"Practical Maya Programming with Python" is a practical tutorial packed with plenty of examples and sample projects which guides you through building reusable, independent modules and handling unexpected errors. If you are a developer looking to build a powerful system using Python and Maya's capabilities, then this book is for you. Practical Maya Programming with Python is perfect for intermediate users with basic experience in Python and Maya who want to better their knowledge and skills.
R 1,661.00
Programming Web Services with XML-RPC
This text introduces the simple but powerful capabilities of XML-RPC, a system for remote procedure calls built on XML and the HTTP protocol. XML-RPC lets developers connect programs running on different computers with a minimum of fuss, by wrapping procedure calls in XML and establishing simple pathways for calling functions. With XML-RPC, Java programs can talk to Perl scripts, which can talk to Python programs, ASP applications, and so on. Developers can provide access to functionality without having to worry about the system on the other end, so it's easy to create Web services. This book supplies the details of both the XML-RPC specification and various XML-RPC implementations, so you can get started developing distributed applications in Java, Perl, Python, ASP, or PHP.
R 798.00
Hands-On Predictive Analytics with Python
Step-by-step guide to build high performing predictive applications Key FeaturesUse the Python data analytics ecosystem to implement end-to-end predictive analytics projectsExplore advanced predictive modeling algorithms with an emphasis on theory with intuitive explanationsLearn to deploy a predictive model's results as an interactive applicationBook DescriptionPredictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages.The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model.Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics.By the end of this book, you will be all set to build high-performance predictive analytics solutions using Python programming.What you will learnGet to grips with the main concepts and principles of predictive analyticsLearn about the stages involved in producing complete predictive analytics solutionsUnderstand how to define a problem, propose a solution, and prepare a datasetUse visualizations to explore relationships and gain insights into the datasetLearn to build regression and classification models using scikit-learnUse Keras to build powerful neural network models that produce accurate predictionsLearn to serve a model's predictions as a web applicationWho this book is forThis book is for data analysts, data scientists, data engineers, and Python developers who want to learn about predictive modeling and would like to implement predictive analytics solutions using Python's data stack. People from other backgrounds who would like to enter this exciting field will greatly benefit from reading this book. All you need is to be proficient in Python programming and have a basic understanding of statistics and college-level algebra.
R 1,661.00
Foundations of Python Network Programming
Foundations of Python Network Programming, Third Edition, covers all of the classic topics found in the second edition of this book, including network protocols, network data and errors, email, server architecture, and HTTP and web applications, plus updates for Python 3.Some of the new topics in this edition include:• Extensive coverage of the updated SSL support in Python 3• How to write your own asynchronous I/O loop.• An overview of the "asyncio" framework that comes with Python 3.4.• How the Flask web framework connects URLs to your Python code.• How cross-site scripting and cross-site request forgery can be used to attack your web site, and how to protect against them.• How a full-stack web framework like Django can automate the round trip from your database to the screen and back.If you're a Python programmer who needs a deep understanding of how to use Python for network-related tasks and applications, this is the book for you. From web application developers, to systems integrators, to system administrators—this book has everything that you need to know.
R 1,839.59
Quick Data Structures
If you want to upgrade your programming skills, the most important thing you need is a solid understanding of fundamental data structures. The proper choice of data structures distinguishes excellent programmers from merely competent ones.As an experienced programmer, you use data structures—at least arrays—all the time. However, you may not be familiar with hash tables, trees and binary trees, priority queues, directed and undirected graphs, and other data structures at your disposal.A good choice of data structures will simplify your job, not complicate it. Your code will be not only faster but also easier to understand and debug. There is no downside to using the right data structures for the job.This book Provides an understanding of the fundamental building blocks of data structures Describes the construction and use of all common data structures Explains the simple math required for selecting efficient data structures Equips you with everything you need to choose data structures or devise appropriate new ones
R 1,436.43
R 1,099.00
R 1,140.00
R 518.00
Learn Quantum Computing with Python and IBM Quantum Experience
A step-by-step guide to learning the implementation and associated methodologies in quantum computing with the help of the IBM Quantum Experience, Qiskit, and Python that will have you up and running and productive in no timeKey FeaturesDetermine the difference between classical computers and quantum computersUnderstand the quantum computational principles such as superposition and entanglement and how they are leveraged on IBM Quantum Experience systemsRun your own quantum experiments and applications by integrating with QiskitBook DescriptionIBM Quantum Experience is a platform that enables developers to learn the basics of quantum computing by allowing them to run experiments on a quantum computing simulator and a real quantum computer. This book will explain the basic principles of quantum mechanics, the principles involved in quantum computing, and the implementation of quantum algorithms and experiments on IBM's quantum processors. You will start working with simple programs that illustrate quantum computing principles and slowly work your way up to more complex programs and algorithms that leverage quantum computing. As you build on your knowledge, you'll understand the functionality of IBM Quantum Experience and the various resources it offers. Furthermore, you'll not only learn the differences between the various quantum computers but also the various simulators available. Later, you'll explore the basics of quantum computing, quantum volume, and a few basic algorithms, all while optimally using the resources available on IBM Quantum Experience. By the end of this book, you'll learn how to build quantum programs on your own and have gained practical quantum computing skills that you can apply to your business.What you will learnExplore quantum computational principles such as superposition and quantum entanglementBecome familiar with the contents and layout of the IBM Quantum ExperienceUnderstand quantum gates and how they operate on qubitsDiscover the quantum information science kit and its elements such as Terra and AerGet to grips with quantum algorithms such as Bell State, Deutsch-Jozsa, Grover's algorithm, and Shor's algorithmHow to create and visualize a quantum circuitWho this book is forThis book is for Python developers who are looking to learn quantum computing and put their knowledge to use in practical situations with the help of IBM Quantum Experience. Some background in computer science and high-school-level physics and math is required.
R 1,498.00
R 1,343.00
