Search results for "Handbook of Computer Programming with Python"
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R 965.00
Getting Started with Python
Harness the power of Python objects and data structures to implement algorithms for analyzing your data and efficiently extracting informationKey FeaturesTurn your designs into working software by learning the Python syntaxWrite robust code with a solid understanding of Python data structuresUnderstand when to use the functional or the OOP approachBook DescriptionThis Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests.By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications.This Learning Path includes content from the following Packt products:Learn Python Programming - Second Edition by Fabrizio RomanoPython Data Structures and Algorithms by Benjamin BakaPython 3 Object-Oriented Programming by Dusty PhillipsWhat you will learnUse data structures and control flow to write codeUse functions to bundle together a sequence of instructionsImplement objects in Python by creating classes and defining methodsDesign public interfaces using abstraction, encapsulation and information hidingRaise, define, and manipulate exceptions using special error objectsCreate bulletproof and reliable software by writing unit testsLearn the common programming patterns and algorithms used in PythonWho this book is forIf you are relatively new to coding and want to write scripts or programs to accomplish tasks using Python, or if you are an object-oriented programmer for other languages and seeking a leg up in the world of Python, then this Learning Path is for you. Though not essential, it will help you to have basic knowledge of programming and OOP.
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R 489.00
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 857.00
Python for Microcontrollers: Getting Started with MicroPython
Build and program your own electronics projects with MicroPython in no time!This practical guide offers a hands-on introduction to Python-based microcontroller programming with MicroPython and the open-source Pyboard hardware platform. The book shows, step-by-step, how to set up and interface with the board, install the necessary software, and develop custom MicroPython programs.Written by an experienced hobbyist, Python for Microcontrollers: Getting Started with MicroPython and Pyboard features start-to-finish, DIY projects that clearly demonstrate each technique. You will learn how to use the built-in sensor, store data to an SD card, control the LCD and matrix keyboard, interface with the Web—even build a cool robotic car! From there, you will discover how to assemble, program, and troubleshoot all kinds of entertaining and practical projects of your own. • Serves both as a hobbyists’ guide and as an introduction for engineers and techs • Features clear explanations, well-illustrated examples, and hands-on projects• Written in clear, easy-to-follow language by an experienced maker
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R 580.00
R 717.00
101 Extra Python Challenges with Solutions / Code Listings
Welcome to this second selection of 101 Python challenges from the 101computing.net website. As its predecessor - 101 Python Challenges with solutions / code listing, published in 2017 - the aim of this follow up book is to help you develop and apply your programing skills by solving carefully selected challenges. The book is organised into ten chapters to progressively introduce a range of key procedural programming concepts.
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R 388.00
R 1,107.00
Artificial Intelligence with Python
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around youAbout This Book• Step into the amazing world of intelligent apps using this comprehensive guide• Enter the world of Artificial Intelligence, explore it, and create your own applications• Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no timeWho This Book Is ForThis book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks.What You Will Learn• Realize different classification and regression techniques• Understand the concept of clustering and how to use it to automatically segment data• See how to build an intelligent recommender system• Understand logic programming and how to use it• Build automatic speech recognition systems• Understand the basics of heuristic search and genetic programming• Develop games using Artificial Intelligence• Learn how reinforcement learning works• Discover how to build intelligent applications centered on images, text, and time series data• See how to use deep learning algorithms and build applications based on itIn DetailArtificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications.During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide!Style and approachThis highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
R 1,889.00
Human-Computer Interaction in Game Development with Python
Deepen your understanding of human-computer interaction (HCI) in game development and learn how to develop video games that grab players and don't let them go. This book explores HCI design in computer games to maximize collaborative and interactive functions. You'll first gain a basic introduction to fundamental concepts and practices of HCI before diving into the fundamental concepts of game interface design and technology. You'll learn how to design a gaming interface through practical examples using Python. This is followed by a brief look at how HCI can offer immersive gaming experiences for players and a review of key elements such as interface, usability, user-centered design, and user interface in terms of efficacy. You will also learn how to implement usability aspects in gaming interfaces with examples using Python. Additionally, the book discusses major challenges that game publishers and developers face, and how they can be resolved using HCI techniques. The question of playability is reviewed throughout the game production process. After working through this book's practical examples, you'll have the knowledge required to begin developing compelling, can't-put-the-controller down games of your own. What You'll LearnMaster HCI tools and methodologies Understand the concept of HCI strategies in the game development cycleDevelop a game in Python using the HCI approachUtilize gamification techniques in Human-Computer InteractionGrasp concepts of usability, user experience and user-centered design processes and their application Who This Book Is ForProgrammers, engineers, and students interested in creating and implementing computer games using HCI technologies. Prior experience with game development is recommended.
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R 7,632.00
50 Algorithms Every Programmer Should Know
Delve into the realm of generative AI and large language models (LLMs) while exploring modern deep learning techniques, including LSTMs, GRUs, RNNs with new chapters included in this 50% new edition overhaulPurchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesFamiliarize yourself with advanced deep learning architecturesExplore newer topics, such as handling hidden bias in data and algorithm explainabilityGet to grips with different programming algorithms and choose the right data structures for their optimal implementationBook DescriptionThe ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. This book will help you not only to develop the skills to select and use an algorithm to tackle problems in the real world but also to understand how it works.You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, with the help of practical examples. As you advance, you'll learn about linear programming, page ranking, and graphs, and will then work with machine learning algorithms to understand the math and logic behind them.Case studies will show you how to apply these algorithms optimally before you focus on deep learning algorithms and learn about different types of deep learning models along with their practical use.You will also learn about modern sequential models and their variants, algorithms, methodologies, and architectures that are used to implement Large Language Models (LLMs) such as ChatGPT.Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.By the end of this programming book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.What you will learnDesign algorithms for solving complex problemsBecome familiar with neural networks and deep learning techniquesExplore existing data structures and algorithms found in Python librariesImplement graph algorithms for fraud detection using network analysisDelve into state-of-the-art algorithms for proficient Natural Language Processing illustrated with real-world examplesCreate a recommendation engine that suggests relevant movies to subscribersGrasp the concepts of sequential machine learning models and their foundational role in the development of cutting-edge LLMsWho this book is forThis computer science book is for programmers or developers who want to understand the use of algorithms for problem-solving and writing efficient code.Whether you are a beginner looking to learn the most used algorithms concisely or an experienced programmer looking to explore cutting-edge algorithms in data science, machine learning, and cryptography, you'll find this book useful.Python programming experience is a must, knowledge of data science will be helpful but not n
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R 855.00
Beginning Ethical Hacking with Python
Learn the basics of ethical hacking and gain insights into the logic, algorithms, and syntax of Python. This book will set you up with a foundation that will help you understand the advanced concepts of hacking in the future. Learn Ethical Hacking with Python 3 touches the core issues of cyber security: in the modern world of interconnected computers and the Internet, security is increasingly becoming one of the most important features of programming. Ethical hacking is closely related to Python. For this reason this book is organized in three parts. The first part deals with the basics of ethical hacking; the second part deals with Python 3; and the third part deals with more advanced features of ethical hacking.What You Will LearnDiscover the legal constraints of ethical hacking Work with virtual machines and virtualization Develop skills in Python 3See the importance of networking in ethical hackingGain knowledge of the dark web, hidden Wikipedia, proxy chains, virtual private networks, MAC addresses, and moreWho This Book Is ForBeginners wanting to learn ethical hacking alongside a modular object oriented programming language.
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R 407.00
R 501.00
Scientific Scripting with Python
Learn how to automate your scientific research with Python. This book teaches you the basics of the popular Python scripting language, before delving deep into all aspects of processing data. Python is a simple, yet powerful, programming language similar to Perl, Tcl, and Ruby. It is heavily used in scientific research, and by companies like Google. This book places a strong emphasis on practical techniques for handling data. Although targeted specifically at scientists and engineers, anyone who needs to automate their work flow would find it useful.
R 1,215.56
Practical Data Science with Python 3
Gain insight into essential data science skills in a holistic manner using data engineering and associated scalable computational methods. This book covers the most popular Python 3 frameworks for both local and distributed (in premise and cloud based) processing. Along the way, you will be introduced to many popular open-source frameworks, like, SciPy, scikitlearn, Numba, Apache Spark, etc. The book is structured around examples, so you will grasp core concepts via case studies and Python 3 code.As data science projects gets continuously larger and more complex, software engineering knowledge and experience is crucial to produce evolvable solutions. You'll see how to create maintainable software for data science and how to document data engineering practices.This book is a good starting point for people who want to gain practical skills to perform data science. All the code will be available in the form of IPython notebooks and Python 3 programs, which allow you to reproduce all analyses from the book and customize them for your own purpose. You'll also benefit from advanced topics like Machine Learning, Recommender Systems, and Security in Data Science.Practical Data Science with Python will empower you analyze data, formulate proper questions, and produce actionable insights, three core stages in most data science endeavors.What You'll LearnPlay the role of a data scientist when completing increasingly challenging exercises using Python 3Work work with proven data science techniques/technologies Review scalable software engineering practices to ramp up data analysis abilities in the realm of Big DataApply theory of probability, statistical inference, and algebra to understand the data science practicesWho This Book Is ForAnyone who would like to embark into the realm of data science using Python 3.
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R 4,274.00
Python Polars: The Definitive Guide
Want to speed up your data analysis and work with larger-than-memory datasets? Python Polars offers a blazingly fast, multithreaded, and elegant API for data loading, manipulation, and processing. With this hands-on guide, you'll walk through every aspect of Polars and learn how to tackle practical use cases using real-world datasets. Jeroen Janssens and Thijs Nieuwdorp from Xomnia in Amsterdam show you how this superfast DataFrame library is perfect for efficient data wrangling, ETL pipelines, and so much more. This book helps you quickly learn the syntax and understand Polars' underlying concepts. You don't need to have experience with pandas or Spark, but if you do, this book will help you make a smooth transition. With this definitive guide at your side, you'll be able to: Process larger-than-memory datasets at record speed Apply the eager, lazy, and streaming APIs of Polars and decide when to use them Transition smoothly from pandas or Spark to Polars Integrate Polars into your existing code base Work with Arrow and Parquet to efficiently read and write data Translate complex ETL tasks into efficient and elegant queries
R 1,824.00
Marketing Research With R And Python
This book is meant for readers with little or no experience in programming in R and Python, who wish to quickly learn what is necessary, and be able to conduct marketing research by running tests easily in R or Python.A number of marketing research textbooks have been using SPSS or SAS for many years. Conversely, R and Python can be downloaded and installed in a personal computer for free. Instructors and students do not have to go to a computer room in a university to use SPSS or SAS anymore. Instead, students can run R or Python on their personal computers.For any company, growth comes either from organic growth of existing products, or from launching successful new products. Due to competition in the marketplace, each company's marketer must determine whether or not it is time to develop and launch a new product:This book covers important frameworks and concepts of marketing research for developing a new product.
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R 1,026.00
R 428.00
Orange Book of Machine Learning Green Edition
Learn supervised machine learning for tabular data using Python, pandas, scikit-learn, CatBoost, LightGBM, XGBoost, TabPFN, and TabICL for regression, classification, and predictive modelingKey FeaturesExplore, clean, and prepare tabular datasets for machine learning workflowsBuild regression and classification models using modern machine learning toolsImprove predictions with calibration, conformal intervals, and optimization techniquesBook DescriptionMaster the essential tools and techniques for supervised machine learning on tabular data with this practical guide to regression and classification. Through clear explanations, code snippets, and hands-on notebooks, you'll learn how to use Python and leading machine learning libraries, including pandas, scikit-learn, CatBoost, LightGBM, XGBoost, TabPFN, and TabICL, to build predictive models for real-world datasets.The book covers the complete workflow, from data exploration and cleaning to model development, evaluation, and optimization. You'll learn how to perform regression analysis for accurate point predictions and estimate uncertainty using conformal prediction intervals. For classification tasks, you'll explore probabilistic predictions and calibration techniques to improve model reliability. You'll also discover practical approaches to feature engineering, feature selection, and hyperparameter optimization to enhance model performance. In addition, the book introduces tabular foundation models and in-context learning techniques, providing insight into the latest advances in machine learning for structured data.By the end of the book, you'll have the skills and confidence to develop, evaluate, and deploy supervised machine learning models for a wide range of tabular data applications.What you will learnPerform exploratory data analysis and data cleaningApply cross-validation for reliable model evaluationBuild regression models and prediction intervalsDevelop calibrated probabilistic classification modelsOptimize models through hyperparameter tuningEngineer and select features for improved performanceUse ensemble learning methods effectivelyExplore tabular foundation models and in-context learningWho this book is forThis book is designed for motivated self-learners, university students studying applied machine learning, junior data scientists, and academic researchers looking to incorporate machine learning into their analytical workflows. Readers should have a basic familiarity with Python and data analysis concepts. Whether you're developing predictive models for business, research, or educational purposes, this book provides the practical guidance needed to apply modern machine learning techniques to structured and tabular datasets.
R 1,303.00
R 2,959.71
Python GUI Programming Cookbook
Over 80 object-oriented recipes to help you create mind-blowing GUIs in PythonAbout This Book• Use object-oriented programming to develop amazing GUIs in Python• Create a working GUI project as a central resource for developing your Python GUIs• Packed with easy-to-follow recipes to help you develop code using the latest released version of PythonWho This Book Is ForIf you are a Python programmer with intermediate level knowledge of GUI programming and want to learn how to create beautiful, effective, and responsive GUIs using the freely available Python GUI frameworks, this book is for you.What You Will Learn• Create amazing GUIs with Python's built-in Tkinter module• Customize the GUIs by using layout managers to arrange the GUI widgets• Advance to an object-oriented programming style using Python• Develop beautiful charts using the free Matplotlib Python module• Use threading in a networked environment to make the GUIs responsive• Discover ways to connect the GUIs to a database• Understand how unit tests can be created and internationalize the GUI• Extend the GUIs with free Python frameworks using best practices In DetailPython is a multi-domain, interpreted programming language. It is a widely used general-purpose, high-level programming language. It is often used as a scripting language because of its forgiving syntax and compatibility with a wide variety of different eco-systems. Its flexible syntax enables developers to write short scripts while at the same time, they can use object-oriented concepts to develop very large projects.Python GUI Programming Cookbook follows a task-based approach to help you create beautiful and very effective GUIs with the least amount of code necessary. This book uses the simplest programming style, using the fewest lines of code to create a GUI in Python, and then advances to using object-oriented programming in later chapters. If you are new to object-oriented programming (OOP), this book will teach you how to take advantage of the OOP coding style in the context of creating GUIs written in Python.Throughout the book, you will develop an entire GUI application, building recipe upon recipe, connecting the GUI to a database. In the later chapters, you will explore additional Python GUI frameworks, using best practices. You will also learn how to use threading to ensure your GUI doesn't go unresponsive.By the end of the book, you will be an expert in Python GUI programming to develop a common set of GUI applications.Style and approachEvery recipe in this programming cookbook solves a problem you might encounter in your programming career. At the same time, most of the recipes build on each other to create an entire, real-life GUI application.
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R 684.00
