Search results for "Master Multi-Paradigm Python Programming"
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Hands-On Python Natural Language Processing
Get well-versed with traditional as well as modern natural language processing concepts and techniquesKey FeaturesPerform various NLP tasks to build linguistic applications using Python librariesUnderstand, analyze, and generate text to provide accurate resultsInterpret human language using various NLP concepts, methodologies, and toolsBook DescriptionNatural Language Processing (NLP) is the subfield in computational linguistics that enables computers to understand, process, and analyze text. This book caters to the unmet demand for hands-on training of NLP concepts and provides exposure to real-world applications along with a solid theoretical grounding.This book starts by introducing you to the field of NLP and its applications, along with the modern Python libraries that you'll use to build your NLP-powered apps. With the help of practical examples, you’ll learn how to build reasonably sophisticated NLP applications, and cover various methodologies and challenges in deploying NLP applications in the real world. You'll cover key NLP tasks such as text classification, semantic embedding, sentiment analysis, machine translation, and developing a chatbot using machine learning and deep learning techniques. The book will also help you discover how machine learning techniques play a vital role in making your linguistic apps smart. Every chapter is accompanied by examples of real-world applications to help you build impressive NLP applications of your own.By the end of this NLP book, you’ll be able to work with language data, use machine learning to identify patterns in text, and get acquainted with the advancements in NLP.What you will learnUnderstand how NLP powers modern applicationsExplore key NLP techniques to build your natural language vocabularyTransform text data into mathematical data structures and learn how to improve text mining modelsDiscover how various neural network architectures work with natural language dataGet the hang of building sophisticated text processing models using machine learning and deep learningCheck out state-of-the-art architectures that have revolutionized research in the NLP domainWho this book is forThis NLP Python book is for anyone looking to learn NLP’s theoretical and practical aspects alike. It starts with the basics and gradually covers advanced concepts to make it easy to follow for readers with varying levels of NLP proficiency. This comprehensive guide will help you develop a thorough understanding of the NLP methodologies for building linguistic applications; however, working knowledge of Python programming language and high school level mathematics is expected.
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Python Practice Lab
A guide to learning basic programming by writing fun, working programs that gradually become more complexThis classroom-tested, workbook-style text teaches basic programming by guiding readers to write Python programs that mimic interactive chatbots. Unlike textbooks with opaque examples explained in dry, monotonous code, Python Practice Lab engages readers immediately, with more than thirty motivating and hands-on examples. Readers learn by writing fun, working programs that gradually become more difficult as new concepts are introduced. Most exercises are open ended, promoting creativity in the process of learning. Along with coding practice, the book offers brief introductions to a range of other topics in computer science, including recommendation systems, computer vision, and big data, and relates these subjects to the programming concepts covered in the book. Python Practice Lab will be an essential resource for anyone who wants to learn to program, instructors teaching Python to beginners, and students who want to supplement their coursework by building complete and functional programs.Uses natural language and text strings rather than math as the main building blocks for learning about program structureRewrites code comprehension exercises in equivalent code with inclusive and approachable variables rather than terse, single-letter variablesChallenges readers to write a full program in each chapterPresents a selection of projects at the end of the book that integrates the concepts introduced in previous chapters
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Multi-Agent Search under Uncertainty
Plan optimal multi-robot search paths despite imperfect sensor information When multiple robots must locate targets in presence of false positive and false negative detection errors, path planning becomes extraordinarily complex. Multi-Agent Search under Uncertainty addresses this challenge directly. Written by the researchers with combined expertise spanning defense systems, applied mathematics, and machine learning, this book delivers both theoretical foundations in search and screening theory and ready-to-use algorithms for practical implementation. The book covers cooperative search and navigation methods for autonomous mobile agents operating with incomplete or noisy information. Readers learn how Deep Q-Learning enables robots to develop complex behaviors through trial-and-error interactions rather than pre-programmed instructions. Applications span search and rescue operations, military surveillance, environmental monitoring, and security systems. An accompanying website provides Python code for simulation practice. Key topics include: Value-based Q-Learning methods where robots learn expected rewards for specific actions in given states under sensor uncertainty conditionsMulti-agent reinforcement learning approaches for swarm robotics where multiple robots learn cooperatively to accomplish collaborative search tasksDeep reinforcement learning using neural networks to process high-dimensional sensory inputs and execute complex search and tracking behaviorsAlgorithms for finding and tracking both stationary and moving targets while minimizing detection time despite false negative and positive readingsTheoretical contributions to search and screening theory alongside practical algorithms validated in autonomous robotic systems development Designed for graduate students and researchers in robotics and reinforcement learning, this book bridges advanced theory with practical application. Professional developers building autonomous systems will find algorithms tested in real-world robotic development.
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Robust Python
Does it seem like your Python projects are getting bigger and bigger? Are you feeling the pain as your codebase expands and gets tougher to debug and maintain? Python is an easy language to learn and use, but that also means systems can quickly grow beyond comprehension. Thankfully, Python has features to help developers overcome maintainability woes.In this practical book, author Patrick Viafore shows you how to use Python's type system to the max. You'll look at user-defined types, such as classes and enums, and Python's type hinting system. You'll also learn how to make Python extensible and how to use a comprehensive testing strategy as a safety net. With these tips and techniques, you'll write clearer and more maintainable code.Learn why types are essential in modern development ecosystemsUnderstand how type choices such as classes, dictionaries, and enums reflect specific intentsMake Python extensible for the future without adding bloatUse popular Python tools to increase the safety and robustness of your codebaseEvaluate current code to detect common maintainability gotchasBuild a safety net around your codebase with linters and tests
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Multi-Paradigm Programming using C++
Aimed mainly at students, this self-contained reference book on C++ is of superb educational value. Starting from scratch, Vermeir explains the idea of address, value and type in C++ before quickly moving on to cover the more important aspects of the language such as classes, templates, generic programming and inheritance. He includes recent developments in C++, such as STL and the iostream library. There is also a chapter devoted to program design principles. By using plenty of examples the reader is stimulated and inspired to see how they can use what they have learnt in other more sophisticated applications. All the examples from the text, including some larger example programs are available on the author's website.
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Practical Python Programming for IoT
Leverage Python and Raspberry Pi to create complex IoT applications capable of creating and detecting movement and measuring distance, light, and a host of other environmental conditionsKey FeaturesLearn the fundamentals of electronics and how to integrate them with a Raspberry PiUnderstand how to build RESTful APIs, WebSocket APIs, and MQTT-based applicationsExplore alternative approaches to structuring IoT applications with PythonBook DescriptionThe age of connected devices is here, be it fitness bands or smart homes. It's now more important than ever to understand how hardware components interact with the internet to collect and analyze user data. The Internet of Things (IoT), combined with the popular open source language Python, can be used to build powerful and intelligent IoT systems with intuitive interfaces. This book consists of three parts, with the first focusing on the "Internet" component of IoT. You'll get to grips with end-to-end IoT app development to control an LED over the internet, before learning how to build RESTful APIs, WebSocket APIs, and MQTT services in Python. The second part delves into the fundamentals behind electronics and GPIO interfacing. As you progress to the last part, you'll focus on the "Things" aspect of IoT, where you will learn how to connect and control a range of electronic sensors and actuators using Python. You'll also explore a variety of topics, such as motor control, ultrasonic sensors, and temperature measurement. Finally, you'll get up to speed with advanced IoT programming techniques in Python, integrate with IoT visualization and automation platforms, and build a comprehensive IoT project. By the end of this book, you'll be well-versed with IoT development and have the knowledge you need to build sophisticated IoT systems using Python.What you will learnUnderstand electronic interfacing with Raspberry Pi from scratchGain knowledge of building sensor and actuator electronic circuitsStructure your code in Python using Async IO, pub/sub models, and moreAutomate real-world IoT projects using sensor and actuator integrationIntegrate electronics with ThingSpeak and IFTTT to enable automationBuild and use RESTful APIs, WebSockets, and MQTT with sensors and actuatorsSet up a Raspberry Pi and Python development environment for IoT projectsWho this book is forThis IoT Python book is for application developers, IoT professionals, or anyone interested in building IoT applications using the Python programming language. It will also be particularly helpful for mid to senior-level software engineers who are experienced in desktop, web, and mobile development, but have little to no experience of electronics, physical computing, and IoT.
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Thoughtful Machine Learning with Python
Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext. Featuring graphs and highlighted code examples throughout, the book features tests with Python's Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you're a software engineer or business analyst interested in data science, this book will help you: Reference real-world examples to test each algorithm through engaging, hands-on exercises Apply test-driven development (TDD) to write and run tests before you start coding Explore techniques for improving your machine-learning models with data extraction and feature development Watch out for the risks of machine learning, such as underfitting or overfitting data Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms
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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.
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Object-oriented Programming Languages and Event-driven Programming
Essential concepts of programming language design and implementation are explained and illustrated in the context of the object-oriented programming language (OOPL) paradigm. Written with the upper-level undergraduate student in mind, the text begins with an introductory chapter that summarizes the essential features of an OOPL, then widens the discussion to categorize the other major paradigms, introduce the important issues, and define the essential terms. After a brief second chapter on event-driven programming (EDP), subsequent chapters are built around case studies in each of the languages Smalltalk, C++, Java, C#, and Python. Included in each case study is a discussion of the accompanying libraries, including the essential container classes. For each language, one important event-driven library is singled out and studied. Sufficient information is given so that students can complete an event-driven project in any of the given languages. After completing the course the student should have a solid set of skills in each language the instructor chooses to cover, a comprehensive overview of how these languages relate to each other, and an appreciation of the major issues in OOPL design.Key Features:Provides essential coverage of Smalltalk origins, syntax, and semantics, a valuable asset for students wanting to understand the hybrid Objective C language Provides detailed case studies of Smalltalk, Java, C++, C#, and Python and features a side-by-side development of the Java and C++ languages--highlighting their similarities and differencesSets the discussion in a historical framework, tracing the roots of the OOPLs back to Simula 67.Provides broad-based coverage of all languages, imparting essential skills as well as an appreciation for each language's design philosophyIncludes chapter summary, review questions, chapter exercises, an appendix with event-driven projects, and instructor resources
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50 Algorithms Every Programmer Should Know - Second Edition
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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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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