Search results for "master multi-paradigm python programming"
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Hands-On Object-Oriented Programming
Learn how to easily design and implement a software system using object-oriented programming. Through hands-on activities, this book equips you with the real-world practice needed to master OOP skills that can be applied universally across any programming language. This book is dedicated to bridging the gap between theoretical concepts and practical implementation in software development using OOP. Readers will first understand the importance of OOP in handling software complexities before learning how to model real-world problems through access control, extendible object design, and object relationships. Specifically, the author discusses how to use inheritance, association, and polymorphism concepts for implementing reusable and easy-to-use complex software. More importantly, this book covers design patterns and event-driven programming for learning how to model complex interactions among various objects of the software system to implement various use cases. Unlike existing books on OOP which teach syntax and semantics through standard examples, this book leverages an immersive learning experience through a variety of real-world use cases, applications, games, and system software. While written in C++, the skills can be applied to any OOP language of the reader's preference. The book's last chapters will quickly introduce Python and Solidity languages for learning advanced technologies. By the end, novice and seasoned developers will know how to implement practical and reusable software systems with confidence. What You Will Learn Apply OOP concepts through real-time use cases: games, applications software (online shopping, reservations, etc.), system software (protocols, simulators, etc.), and modeling and implementation using C+Design and implement reusable and extendible software with OOPUnderstand the importance of design patterns and learn how to use them for solving real-time issuesUse event-driven programming for implementing complete interactions of complex application software, system software, and simulatorsImplement OOP using C++ features and discover Python and Solidity constructs for OOP Who This Book Is For Beginners and intermediate software developers with basic programming knowledge to quickly learn OOP concepts with C++. Advanced users will find it useful for quickly exploring best-design principles, patterns, and event-driven programming for implementing complex software systems.
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Foundations of Programming, Statistics, and Machine Learning for Business Analytics
Business Analysts and Data Scientists are in huge demand, as global companies seek to digitally transform themselves and leverage their data resources to realize competitive advantage.This book covers all the fundamentals, from statistics to programming to business applications, to equip you with the solid foundational knowledge needed to progress in business analytics. Assuming no prior knowledge of programming or statistics, this book takes a simple step-by-step approach which makes potentially intimidating topics easy to understand, by keeping Maths to a minimum and including examples of business analytics in practice.Key features:· Introduces programming fundamentals using R and Python· Covers data structures, data management and manipulation and data visualization· Includes interactive coding notebooks so that you can build up your programming skills progressivelySuitable as an essential text for undergraduate and postgraduate students studying Business Analytics or as pre-reading for students studying Data Science.Ram Gopal is Pro-Dean and Professor of Information Systems at the University of Warwick.Daniel Philps is an Artificial Intelligence Researcher and Head of Rothko Investment Strategies.Tillman Weyde is Senior Lecturer at City, University of London.
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Quick Functional Programming
Why learn functional programming? Isn’t that some complicated ivory-tower technique used only in obscure languages like Haskell?In fact, functional programming is actually very simple. It’s also very powerful, as Haskell demonstrates by throwing away all the conventional programming tools and using only functional programming features. But it doesn’t have to be done that way.Functional programming is a power tool that you can use in addition to all your usual tools, to whatever extent your current mainstream language supports it. Most languages have at least basic support.In this book we use Python and Java and, as a bonus, Scala. If you prefer another language, there will be minor differences in syntax, but the concepts are the same.Give functional programming a try. You may be surprised how much a single power tool can help you in your day-to-day programming.
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Fortran Programming in easy steps
Master the essentials of modernFortran with Fortran Programming in easy steps.Written for all ages, and all skill levels, this guide will help you quicklyset up your coding environment and start writing Fortran programs with theFortran programming language and the modern Intel IFX Fortran compiler rightaway. Learn how to:Store information using datastructures.Control program flow using controlstructures. Build re-usable blocks of code inprogram functions for efficiency. Utilize data abstractionfor Object Oriented Programming (OOP). Implement parallelprogramming for faster, concurrent execution in your programs. Color-coded examples make learningeven easier, and all source code is available to download free – so you cancheck your work as you go!This primer is your gateway tomastering high-performance computing for today’s needs. Stay ahead in yourcoding career!
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Programming Erlang 2ed
A multi-user game, web site, cloud application, or networked database can have thousands of users all interacting at the same time. You need a powerful, industrial-strength tool to handle the really hard problems inherent in parallel, concurrent environments. You need Erlang. In this second edition of the bestselling Programming Erlang, you'll learn how to write parallel programs that scale effortlessly on multicore systems. Using Erlang, you'll be surprised at how easy it becomes to deal with parallel problems, and how much faster and more efficiently your programs run. That's because Erlang uses sets of parallel processes-not a single sequential process, as found in most programming languages. Joe Armstrong, creator of Erlang, introduces this powerful language in small steps, giving you a complete overview of Erlang and how to use it in common scenarios. You'll start with sequential programming, move to parallel programming and handling errors in parallel programs, and learn to work confidently with distributed programming and the standard Erlang/Open Telecom Platform (OTP) frameworks. You need no previous knowledge of functional or parallel programming.The chapters are packed with hands-on, real-world tutorial examples and insider tips and advice, and finish with exercises for both beginning and advanced users. The second edition has been extensively rewritten. New to this edition are seven chapters covering the latest Erlang features: maps, the type system and the Dialyzer, WebSockets, programming idioms, and a new stand-alone execution environment. You'll write programs that dynamically detect and correct errors, and that can be upgraded without stopping the system. There's also coverage of rebar (the de facto Erlang build system), and information on how to share and use Erlang projects on github, illustrated with examples from cowboy and bitcask. Erlang will change your view of the world, and of how you program.
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Programming Microsoft Dynamics 365 Business Central
Explore the fundamentals of Dynamics 365 Business Central and the Visual Studio Code development environment with the help of useful examples and case studiesKey FeaturesTailor your applications to best suit the needs of your businessExplore the latest features of Business Central with examples curated by industry expertsIntegrate Business Central features in your applications with this comprehensive guideBook DescriptionMicrosoft Dynamics 365 Business Central is a full ERP business solution suite with a robust set of development tools to support customization and enhancement. These tools can be used to tailor Business Central's in-built applications to support complete management functions for finance, supply chain, manufacturing, and operations.Using a case study approach, this book will introduce you to Dynamics 365 Business Central and Visual Studio Code development tools to help you become a productive Business Central developer. You'll also learn how to evaluate a product's development capabilities and manage Business Central-based development and implementation. You'll explore application structure, the construction of and uses for each object type, and how it all fits together to build apps that meet special business requirements.By the end of this book, you'll understand how to design and develop high-quality software using the Visual Studio Code development environment, the AL language paired with the improved editor, patterns, and features.What you will learnProgramming using the AL language in the Visual Studio Code development environmentExplore functional design and development using ALHow to build interactive pages and learn how to extract data for usersHow to use best practices to design and develop modifications for new functionality integrated with the standard Business Central softwareBecome familiar with deploying the broad range of components available in a Business Central systemCreate robust, viable systems to address specific business requirementsWho this book is forIf you want to learn about Dynamics 365 Business Central's powerful and extensive built-in development capabilities, this is the book for you. ERP consultants and managers of Business Central development will also find this book helpful. Although you aren't expected to have worked with Dynamics Business Central, basic understanding of programming and familiarity with business application software will help you understand the concepts covered in this book.
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Python for Signal Processing
This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to “experiment and learn” as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future. For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.
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Computer Science From Scratch
Computer science can feel unapproachable for those without a formal CS education. Fun Computer Science Projects in Python pulls back that curtain, illuminating several foundational CS concepts through creative, hands-on projects. Each of the 7 projects is presented in a code-centric tutorial that gently introduces topics like interpreters, emulators, and machine learning without getting bogged down by complex theory. The projects showcase advanced Python language features and clean code principles while exploring interesting algorithms. Chapters conclude with discussions of real-world applications of the topic and proposed exercises to extend the reader's skills. Covers Python 3.x
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Python: Deeper Insights into Machine Learning
Leverage benefits of machine learning techniques using PythonAbout This Book* Improve and optimise machine learning systems using effective strategies.* Develop a strategy to deal with a large amount of data.* Use of Python code for implementing a range of machine learning algorithms and techniques.Who This Book Is ForThis title is for data scientist and researchers who are already into the field of data science and want to see machine learning in action and explore its real-world application. Prior knowledge of Python programming and mathematics is must with basic knowledge of machine learning concepts.What You Will Learn* Learn to write clean and elegant Python code that will optimize the strength of your algorithms* Uncover hidden patterns and structures in data with clustering* Improve accuracy and consistency of results using powerful feature engineering techniques* Gain practical and theoretical understanding of cutting-edge deep learning algorithms* Solve unique tasks by building models* Get grips on the machine learning design processIn DetailMachine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. It is one of the fastest growing trends in modern computing, and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project.The idea is to prepare a learning path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems.The course begins with getting your Python fundamentals nailed down. It focuses on answering the right questions that cove a wide range of powerful Python libraries, including scikit-learn Theano and Keras.After getting familiar with Python core concepts, it's time to dive into the field of data science. You will further gain a solid foundation on the machine learning design and also learn to customize models for solving problems.At a later stage, you will get a grip on more advanced techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering.Style and approachThis course includes all the resources that will help you jump into the data science field with Python. The aim is to walk through the elements of Python covering powerful machine learning libraries. This course will explain important machine learning models in a step-by-step manner. Each topic is well explained with real-world applications with detailed guidance.Through this comprehensive guide, you will be able to explore machine learning techniques.
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Advanced Applications of Python Data Structures and Algorithms
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision.Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
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Programming Languages and Systems
The open access book set LNCS 16501 + LNCS 16502 constitutes the proceedings of the 35th European Symposium on Programming, ESOP 2026, which was held as part of the International Joint Conferences on Theory and Practice of Software, ETAPS 2026, in Turin, Italy, during April 11-16, 2026.The 31 full papers included in the proceedings, together with one invited talk, were carefully reviewed and selected from 94 submissions. They deal with fundamental issues in the specification, design, analysis and implementation of programming languages and systems, such as programming paradigms and styles; methods and tools to write and specify programs and languages; methods and tools for reasoning about programs; programming systems design and implementation.
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AI and ML for Coders in Pytorch
Eager to learn AI and machine learning but unsure where to start? Laurence Moroney's hands-on, code-first guide demystifies complex AI concepts without relying on advanced mathematics. Designed for programmers, it focuses on practical applications using PyTorch, helping you build real-world models without feeling overwhelmed.From computer vision and natural language processing (NLP) to generative AI with Hugging Face Transformers, this book equips you with the skills most in demand for AI development today. You'll also learn how to deploy your models across the web and cloud confidently.Gain the confidence to apply AI without needing advanced math or theory expertiseDiscover how to build AI models for computer vision, NLP, and sequence modeling with PyTorchLearn generative AI techniques with Hugging Face Diffusers and Transformers
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Python Projects for Raspberry Pi and Pico
Computers are no longer beige boxes that sit on our desks or foldable aluminium books - they are embedded into almost everything we own. Our doorbells, kitchen gadgets, vacuum cleaners, and media players are all powerful computing devices running software that someone has written. Learning to program no longer means learning to control things on a screen, it means learning to control hardware that interacts with the real world.The Raspberry Pi platforms offer a wide range of powerful ways to interact with the world, but sometimes the choice can be bewildering. Using the flexible Python programming language, we'll show you how to get the most out of both the Pico range of microcontrollers and the larger Linux-powered Raspberry Pi boards.Learn how to:Select the perfect hardwareControl sensors and motorsBuild a smart weather stationMake your own games consoleEmbed Artificial Intelligence into your projectsYou'll then be able to take the skills you've learned in the book and build your own projects powered by Raspberry Pi hardware. This book is perfect for intermediate users who want to sense, control and take over the world with homemade digital assistants, smart devices, and robots.
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Machine Learning Guide for Oil and Gas Using Python
Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges.
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