Search results for "master multi-paradigm python programming"
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Data Structures for Engineers and Scientists Using Python
The text covers the fundamentals of Python programming and the implementation of data structures using Python programming with the help of worked-out examples. It provides a learning tool for engineers as well as for researchers and scientists of advanced level. The text further discusses important concepts such as polynomial manipulation, sparse matrices, implementation of stack using the queue model and topological sorting.This book:Discusses the implementation of various data structures such as an array, stack, queue, tree and graph along with sorting and searching algorithms. Includes programming tips to highlight important concepts and help readers avoid common programming errors. Presents each concept of data structure with a different approach and implements the same using Python programming. Offers rich chapter-end pedagogy including objective-type questions (with answers), review questions and programming exercises to facilitate review. Covers fundamentals of Python up to object-oriented concepts including regular expression. It is primarily written for senior undergraduate, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering and information technology.
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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
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Distributed Programming Paradigms with Cryptography Applications
This monograph describes a programming methodology based upon programming paradigms and generic programs and demonstates how distributed application programs can be developed by simple substitution of data structures and sequential procedures. The author introduces generic programs for two paradigms and shows how to derive new distributed programs for several applications related to the RSA cryptosystem, including RSA enciphering and deciphering, prime number generation, and factoring.The book is well-written and easily accessible to the non-expert. The work is an appealing combination of the theory and practice of parallel computing and provides a clear introduction to the theory and practice of RSA cryptography.
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Multicore Programming Using the ParC Language
Multicore Programming Using the ParC Language discusses the principles of practical parallel programming using shared memory on multicore machines. It uses a simple yet powerful parallel dialect of C called ParC as the basic programming language. Designed to be used in an introductory course in parallel programming and covering basic and advanced concepts of parallel programming via ParC examples, the book combines a mixture of research directions, covering issues in parallel operating systems, and compilation techniques relevant for shared memory and multicore machines.Multicore Programming Using the ParC Language provides a firm basis for the ‘delicate art’ of creating efficient parallel programs. Students can exercise parallel programming using a simulation software, which is portable on PC/Unix multicore computers, to gain experience without requiring specialist hardware. Students can also help to cement their learning by completing the great many challenging and exciting exercises which accompany each chapter.
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Programming Language Design Concepts
Explains the concepts underlying programming languages, and demonstrates how these concepts are synthesized in the major paradigms: imperative, OO, concurrent, functional, logic and with recent scripting languages. It gives greatest prominence to the OO paradigm.;Includes numerous examples using C, Java and C++ as exmplar languages Additional case-study languages: Python, Haskell, Prolog and Ada Extensive end-of-chapter exercises with sample solutions on the companion Web site Deepens study by examining the motivation of programming languages not just their features
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Distributed Programming
Distributed Programming: Theory and Practice presents a practical and rigorous method to develop distributed programs that correctly implement their specifications. The method also covers how to write specifications and how to use them. Numerous examples such as bounded buffers, distributed locks, message-passing services, and distributed termination detection illustrate the method. Larger examples include data transfer protocols, distributed shared memory, and TCP network sockets. Distributed Programming: Theory and Practice bridges the gap between books that focus on specific concurrent programming languages and books that focus on distributed algorithms. Programs are written in a "real-life" programming notation, along the lines of Java and Python with explicit instantiation of threads and programs. Students and programmers will see these as programs and not "merely" algorithms in pseudo-code. The programs implement interesting algorithms and solve problems that are large enough to serve as projects in programming classes and software engineering classes. Exercises and examples are included at the end of each chapter with on-line access to the solutions. Distributed Programming: Theory and Practice is designed as an advanced-level text book for students in computer science and electrical engineering. Programmers, software engineers and researchers working in this field will also find this book useful.
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Advanced Machine Learning with Python
Solve challenging data science problems by mastering cutting-edge machine learning techniques in PythonAbout This Book• Resolve complex machine learning problems and explore deep learning• Learn to use Python code for implementing a range of machine learning algorithms and techniques• A practical tutorial that tackles real-world computing problems through a rigorous and effective approachWho This Book Is ForThis title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution, or of entering a Kaggle contest for instance, this book is for you!Prior experience of Python and grounding in some of the core concepts of machine learning would be helpful.What You Will Learn• Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms• Apply your new found skills to solve real problems, through clearly-explained code for every technique and test• Automate large sets of complex data and overcome time-consuming practical challenges• Improve the accuracy of models and your existing input data using powerful feature engineering techniques• Use multiple learning techniques together to improve the consistency of results• Understand the hidden structure of datasets using a range of unsupervised techniques• Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach• Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models togetherIn DetailDesigned to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data.The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce.This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano.By this end of th
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Natural Language Processing with Python
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: * Extract information from unstructured text, either to guess the topic or identify "named entities" * Analyze linguistic structure in text, including parsing and semantic analysis * Access popular linguistic databases, including WordNet and treebanks * Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library.If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
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Mastering Financial Pattern Recognition - Finding and Back-Testing Candlestick Patterns With Python
Candlesticks have become a key component of platforms and charting programs for financial trading. With these charts, traders can learn underlying patterns for interpreting price action history and forecasts. This A-Z guide shows portfolio managers, quants, strategists, and analysts how to use Python to recognize, scan, trade, and back-test the profitability of candlestick patterns. Financial author, trading consultant, and institutional market strategist Sofien Kaabar shows you how to create a candlestick scanner and indicator so you can compare the profitability of these patterns. With this hands-on book, you'll also explore a new type of charting system similar to candlesticks, as well as new patterns that have never been presented before. With this book, you will: Create and understand the conditions required for classic and modern candlestick patterns Learn the market psychology behind them Use a framework to learn how back-testing trading strategies are conducted Explore different charting systems and understand their limitations Import OHLC historical FX data in Python in different time frames Use algorithms to scan for and reproduce patterns Learn a pattern's potential by evaluating its profitability and predictability
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Numerical Methods in Physics with Python
Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject.
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Mathematics and Python Programming
This book contains 120 Python programs and more than 110 illustrations useful both to students of science of the first university courses, as well as high school students and teachers. All the programs and graphics of the book have been developed using free software, which you can obtain free and legally on the internet, so it is not necessary to buy any software. Python is currently the most popular language for teaching introductory computer science courses at top-ranked U.S. universities. You can freely write Python programs whether you are a Windows user or whether you prefer Mac or Linux. A free pdf excerpt is available at our website www.pysamples.com. The buyers of the book can also download the code of the Python programs. The book consists of a detailed introduction to Python, followed by ten chapters of mathematics with its corresponding Python programs, results and graphs.
R 807.68
Mastering PLC Programming
Learn PLC programming from the software perspective to understand advanced concepts such as OOP and HMI development and design reusable, portable, and robust codePurchase of the print or Kindle book includes a free PDF eBookKey FeaturesTake a deep dive into object-oriented PLC programming to gain hands-on knowledgeExplore software engineering concepts such as SDLC, debugging, and SOLID programmingGet a thorough grasp on HMI development to build various HMI projectsBook DescriptionObject-oriented programming (OOP) is a new feature of PLC programming that has taken the automation world by storm. This book provides you with the necessary skills to succeed in the modern automation programming environment.The book is designed in a way to take you through advanced topics such as OOP design, SOLID programming, the software development lifecycle (SDLC), library design, HMI development, general software engineering practices, and more. To hone your programming skills, each chapter has a simulated real-world project that'll enable you to apply the skills you've learned. In all, this book not only covers complex PLC programming topics, but it also removes the financial barrier that comes with most books as all examples utilize free software. This means that to follow along, you DO NOT need to purchase any PLC hardware or software.By the end of this PLC book, you will have what it takes to create long-lasting codebases for any modern automation project.What you will learnFind out how to write PLC programs using advanced programming techniquesExplore OOP concepts for PLC programmingDelve into software engineering topics such as libraries and SOLID programmingExplore HMIs, HMI controls, HMI layouts, and alarmsCreate an HMI project and attach it to a PLC in CODESYSGain hands-on experience by building simulated PLC and HMI projectsWho this book is forThis book is for automaton programmers with a background in software engineering topics such as object-oriented programming and general software engineering knowledge. Automation engineers, software engineers, electrical engineers, PLC technicians, hobbyists, and upper-level university students with an interest in automation or robotics will also find this book useful and interesting. Anyone with a basic knowledge of PLCs can benefit from reading this book.
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Programming in Two Semesters
This highly accessible textbook teaches programming from first principles. In common with many programming courses, it uses Python as the introductory programming language before going on to use Java as the vehicle for more advanced programming concepts.The first part, which teaches Python, covers fundamental programming concepts, such as data types and control structures and functions. It introduces more complex data types such as lists and dictionaries and also deals with file handling. It introduces object-oriented concepts and ends with a case study bringing together all the topics of the first semester. The second part uses Java to teach advanced concepts and centres around object-oriented programming, teaching key object-oriented concepts such as inheritance and polymorphism. The semester again ends with an advanced case study bringing together all the topics of the second semester.Topics and features:Assumes no prior knowledge, and makes the transition from Python to Java a smooth processFeatures numerous exercises and also an illustrative case study for each language Examines procedural and object-oriented methodologies, as well as design principles Covers such advanced topics as interfaces and lambda expressions, exceptions and Collections Includes a chapter on graphics programming in Python using Tkinter Introduces the latest Java technology for graphical interfaces, JavaFXExplains design concepts using UML notation Offering a gentle introduction to the field and assuming no prerequisite background, Programming in Two Semesters is the ideal companion to undergraduate modules in software development or programming. In addition, it will serve as a strong primer for professionals looking to strengthen their knowledge of programming with these languages.
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Python Automation For Dummies
Streamline Your Workflow and Boost Productivity with Python Automation In today's workplaces, there's a high demand for know-how on the Python programming language, especially for writing time-saving scripts that can simplify routine work tasks. Python Automation For Dummies delivers, with simple explanations of how you can use Python to automatically wrangle data files, manage media files, create shortcuts, find and organize web data, and even analyze social media for trends. With this easy-to-follow Dummies guide, you can upskill, expand your productivity, and speed up the process of generating data-driven insights. You'll even learn to enhance your Python automations with AI, for workflows that are faster and smarter. Review the basics of Python coding and follow steps for automating all sorts of tasksManage large file sets, organize and analyze data, and speed up research processesAutomate scheduling and other time-consuming tasks—and optimize work with AIFree up time and resources by automating routine work, so you can foucs on more important issues This is a great Dummies resource for Python developers interested in applying the popular coding language to make workflows more efficient.
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Web Development with Django 6
Create modern, secure websites easily and quickly with Django 6 through realistic case studies updated for the latest async features and modern Python supportKey FeaturesGet to grips with Django 6 functionality, the MVT paradigm, and its new async-powered featuresBuild and extend a book-review site using updated templates, forms, async features, and ORM toolsExplore REST APIs, async views, third-party integrations, testing, and modern deployment optionsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionTired of spending hours on boilerplate code when you should be building features? Django 6 transforms your workflow with major improvements to the Python web ecosystem—from expanded async support to improved form rendering, stronger security, and modern template and ORM capabilities. This book shows you how to take full advantage of these upgrades to build reliable, secure, and high-performance web applications in a structured, hands-on way.You’ll discover Django 6’s power by building an end-to-end case study of developing a website called Bookr, a repository for book reviews that mirrors real development workflows. Through guided practical exercises, you'll learn how to serve static files, implement forms using Django 6’s improved rendering system, handle async views and ORM operations, and manage sessions to create a seamless user experience. You’ll also tackle essential tasks such as authentication, security best practices, and integrating modern front-end tools.By the end of this Django book, you’ll be ready to build and deploy your own scalable, modern Python web applications using Django 6.What you will learnStart a new Django 6 project and define models using the improved ORMWork with function and class-based views using templates to control application behaviorImplement authentication, permissions, and modern session handling techniquesCreate practical forms using Django 6's updated rendering APIBuild RESTful APIs and the JavaScript features that integrate with themConnect to PostgreSQL and run async-ready queries where supportedWho this book is forThis book is for programmers who want to enhance their web development skills with Django 6. You’ll get the most out of it if you already know Python programming and are familiar with JavaScript, HTML, and CSS. This book is especially useful for anyone looking to understand Django’s new async capabilities, modern security features, and production-ready web development patterns.
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