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Название: Edge Intelligence: Deep Learning-enabled edge computing
Автор: Shajulin Benedict
Издательство: IOP Publishing
Год: 2024
Страниц: 277
Язык: английский
Формат: pdf (true), epub
Размер: 31.7 MB

Edge Intelligence: Deep Learning-enabled edge computing is a book that targets researchers and practitioners who are interested in applying intelligence without compromising data privacy. The book reveals the existing edge-AI techniques and forecasts future edge-AI integration methods. The book delves into edge computing architectures after describing relevant basic technologies such as IoT, cloud computing, and other security-related architectures. The book starts with an explanation of all relevant basic technologies. It offers a smooth transition from the basics to insightful practical sessions for practitioners. The ideas of providing innovative ideas and applications in the later part of the book can enthuse researchers and developers to engage themselves in innovating newer products with the application of Edge Intelligence. Part of IOP Series in Next Generation Computing. Edge intelligence is deployed in two broad ways: (i) machine learning-based intelligence; and (ii) deep learning-based intelligence. Deep Learning-based edge intelligence: Deep Learning, in general, is a sub-field of Machine Learning that mimics the learning processes of humans. Our human brains learn different data based on several histories of information. This involves computationally powerful computers or computing devices to learn a large volume of data that arises from data-intensive applications, such as IoT-enabled applications. In recent years, the majority of real-world applications have included Deep Learning algorithms on edge nodes, considering the performance efficiency and learning accuracy with respect to the input regional data. The most widely applied Deep Learning algorithms are convolutional neural networks (CNNs), image segmentation algorithms, generative adversarial networks (GANs), reinforcement learning (RL), and transformers. The application of Deep Learning algorithms on edge-level nodes increases privacy and avoids latency while considering a large chunk of data in an automated fashion.

Название: Python Game Development: Creating Interactive Games With Python And Pygame Library
Автор: Marley Jackson
Издательство: Independently published
Год: 2024
Страниц: 333
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Ever wanted to create your own video games? Imagine designing and coding your very own interactive games, bringing your creative ideas to life with the powerful Python programming language. "Python Game Development: Creating Interactive Games with Python and Pygame Library" is your step-by-step guide to mastering game development, whether you're a beginner or an experienced programmer. Python, renowned for its simplicity and versatility, has gained significant popularity in the realm of game development. Its ease of use, coupled with a rich ecosystem of libraries and frameworks, makes it an attractive choice for both beginners and experienced developers looking to create captivating games. In this chapter, we will delve into the exciting world of game development with Python, exploring the tools, techniques, and concepts that form the foundation of this creative endeavor. Game development with Python opens up a myriad of possibilities, allowing developers to bring their imaginative ideas to life through interactive and engaging gameplay experiences. Whether you are a seasoned programmer or a novice enthusiast, Python offers a welcoming environment for crafting games that captivate players of all ages. Pygame is a cross-platform set of Python modules specifically crafted for writing video games. It is built upon the Simple DirectMedia Layer (SDL) library, which provides low-level access to audio, keyboard, mouse, and graphics hardware. Pygame simplifies game development by abstracting away the complexities of interacting with hardware and allows developers to focus on game logic and design.

Название: Astronomical Python: An introduction to modern scientific programming
Автор: Imad Pasha
Издательство: IOP Publishing
Год: 2024
Страниц: 333
Язык: английский
Формат: pdf (true), epub
Размер: 48.1 MB

Over the past two decades, Python has become the de facto standard language of Data Science both in industry and astronomy (with the exception of simulations and other extreme scale computing problems). This course text is a full introduction to programming in Python with an explicit focus on astrophysical applications. The book covers the fundamentals of Python, including the native data types and operations, and how the language, interpreter, and operating system work together. Leaning heavily on standard packages used in astronomy, the book covers the installation and basic structure of the language and libraries; script writing, conditional statements, loops, and other code structures that allow for complex outcome management; the creation and use of functions and classes within Python; the creation of packages and the methods for re-using, importing, and otherwise standardizing code; and plotting. Finally, the book contains several higher level chapters that carry students from the beginner stage of programming into the intermediate. This book will cover the native data types and operations, and how the language, interpreter, and operating system work together to carry out commands. The book will lean heavily on standard packages (libraries of functions and classes) used in our field, including Numpy, SciPy, Matplotlib, and Astropy. After discussing the installation and basic structure of the language and libraries, the text will move into a discussion of script writing, conditional statements, loops, and other code structures that allow for complex outcome management. The text will then discuss the creation and use of functions and classes within Python, which enables unit-testing and more robust and flexible code creation, and use these tools in a Data Science context on an astronomical survey.

Название: Image Processing with Python: A practical approach
Автор: Irshad Ahmad Ansari, Varun Bajaj
Издательство: IOP Publishing
Год: 2024
Страниц: 300
Язык: английский
Формат: pdf (true), epub
Размер: 38.2 MB

This book explores the domain of image processing using Python, with the help of working examples and accompanying code. Aimed at researchers and advanced students with a knowledge of image processing fundamentals, this book introduces Python programming via image processing and provides numerous hands-on examples and code snippets. The book will enable readers to appreciate the power of Python in this field, write their own code, and implement complex image processing algorithms such as image enhancement, compression, restoration, segmentation, watermarking, and encryption, and be able to incorporate machine learning models using relevant Python libraries. This book is prepared to meet the needs of young researchers and professionals who are about to start their research journey in the domain of image processing. This book will help readers develop their own applications, whether for software-based implementation or simulation and testing before a final hardware implementation. Python for image processing applications has grown tremendously due to its open-source nature and excellent library support. Professionals, students, and researchers working in the image processing domain find it helpful to use pre-existing libraries. They can even create their own library and make it available for others to use. These qualities led to an excellent growth in the popularity of Python.

Название: Mastering Computer Vision with PyTorch and Machine Learning
Автор: Caide Xiao
Издательство: IOP Publishing
Год: 2024
Страниц: 365
Язык: английский
Формат: pdf (true), epub
Размер: 110.5 MB

This book, together with the accompanying Python codes, provides a thorough and extensive guide for mastering advanced computer vision techniques for image processing by using the open-source machine learning framework PyTorch. Known for its user-friendly interface and Python programming style, PyTorch is accessible and one of the most popular tools among researchers and practitioners in the field of Artificial Intelligence. Computer Vision is a field of Artificial Intelligence and Computer Science that focuses on enabling computers to interpret and understand visual information from the world around them. Computer vision and Machine Learning are closely related fields. Machine Learning is used in computer vision to enable computers to automatically find patterns and relationships in large datasets of images and videos. With a focus on practical applications, this book covers essential concepts such as Kullback Leibler divergence, maximum likelihood, convolutional neural networks (CNN), generative adversarial networks (GAN), Wasserstein generative adversarial networks (WGAN), WGAN with gradient penalty (WGAN-GP), information maximizing generative adversarial networks (infoGAN), variational autoencoders (VAE), and their applications for image classification/image generation. Readers will also learn how to leverage the latest computer vision techniques like Yolov8 for object detection, stable diffusion models for image generation, vision transformers for zero-shot object detection, knowledge distillation for compression of neural networks, DINO for self-supervised learning, segment anything models (SAM), NeRF and 3D Gaussian Splatting for 3D scenes synthesis. This book is a valuable resource for professionals, researchers, and students who want to expand their knowledge of advanced computer vision techniques using PyTorch.

Название: Programming WebRTC: Build Real-Time Streaming Applications for the Web
Автор: Karl Stolley
Издательство: Pragmatic Bookshelf
Год: July 2024 (Book version: P1.0)
Страниц: 260
Язык: английский
Формат: pdf (true), epub + Code
Размер: 34.8 MB

Build your own video chat application—but that’s just the beginning. With WebRTC, you’ll create real-time applications to stream any kind of user media and data directly from one browser to another, all built on familiar HTML, CSS, and jаvascript. Power real-time activities like text-based chats, secure peer-to-peer file transfers, collaborative brainstorming sessions—even multiplayer gaming. And you’re not limited to two connected users: an entire chapter of the book is devoted to engineering multipeer WebRTC apps that let groups of people communicate in real time. You’ll create your own video conferencing app. It’s all here. WebRTC is an API exposed in all modern web browsers. After almost a decade of development, the WebRTC specification was finalized, and this book provides faithful coverage of that finalized specification. You’ll start by building a basic but complete WebRTC application for video chatting. Chapter by chapter, you’ll refine that app and its core logic to spin up new and exciting WebRTC-powered apps that will have your users sharing all manner of data with one another, all in real time. No third-party libraries or heavy downloads are required for you or your users: you’ll be writing and strengthening your knowledge of vanilla jаvascript and native browser APIs.

Название: Learn C# Programming by Creating Games with Unity (Beginner): Learn C# and Enjoy the Process
Автор: Patrick Felicia
Издательство: LPF Publishing
Год: 2024
Страниц: 538
Язык: английский
Формат: pdf, epub
Размер: 10.7 MB

Master C# and Game Development with Unity. Are you ready to turn your passion for gaming into a career? This comprehensive guide is your ultimate resource for mastering C# and Unity. Whether you're a beginner or looking to refine your skills, this book offers step-by-step instructions, practical exercises, and real-world projects to help you learn C# programming through the exciting process of game development. Unity makes it possible to create video games without knowing some of the underlying technologies of game development, so that potential game developers only need to focus on the game mechanics and employ a high-level approach to creating games using programming and scripting languages such as C# or jаvascript. The term high-level here refers to the fact that when you create a game with a game engine, you don’t need to worry about how the software will render the game or how it will communicate with the graphics card to optimize the speed of your game.

Название: Explainable Artificial Intelligence for Biomedical and Healthcare Applications
Автор: Aditya Khamparia, Deepak Gupta
Издательство: CRC Press
Серия: Explainable AI (XAI) for Engineering Applications
Год: 2025
Страниц: 303
Язык: английский
Формат: pdf (true)
Размер: 31.5 MB

This reference text helps us understand how the concepts of Explainable Artificial Intelligence (XAI) are used in the medical and healthcare sectors. The text discusses medical robotic systems using XAI and physical devices having autonomous behaviors for medical operations. It explores the usage of XAI for analyzing different types of unique data sets for medical image analysis, medical image registration, medical data synthesis, and information discovery. It covers important topics including XAI for biometric security, genomics, and medical disease diagnosis. Explainable AI is currently on a rapid rise for biomedical and healthcare applications. Because of its advantages in dealing with big, complex amounts of data, explainable AI concepts are applied in many fields and as a critical one, the medical field has a remarkable interest in the use of that sub-field of Artificial Intelligence. Thanks to the use of Machine Learning, vision, and Deep Learning techniques, many improvements have been done in terms of medical data analysis, diagnosis, treatment, and even personal healthcare. There are already many positive results provided by Deep Learning, in the literature of medicine.

Название: Artificial Intelligence: An Introduction to the Big Ideas and their Development, 2nd Edition
Автор: Robert H. Chen, Chelsea Chen
Издательство: CRC Press
Серия: Chapman & Hall/CRC Mathematics and Artificial Intelligence Series
Год: 2025
Страниц: 339
Язык: английский
Формат: pdf (true)
Размер: 14.9 MB

Artificial Intelligence: An Introduction to Big Ideas and their Development, Second Edition guides readers through the history and development of Artificial Intelligence (AI), from its early mathematical beginnings through to the exciting possibilities of its potential future applications. To make this journey as accessible as possible, the authors build their narrative around accounts of some of the more popular and well-known demonstrations of artificial intelligence, including Deep Blue, AlphaGo and even Texas Hold’em, followed by their historical background, so that AI can be seen as a natural development of the mathematics and Computer Science of AI. As the book proceeds, more technical descriptions are presented at a pace that should be suitable for all levels of readers, gradually building a broad and reasonably deep understanding and appreciation for the basic mathematics, physics, and computer science that is rapidly developing Artificial Intelligence as it is today. A Large Language Model (LLM) is essentially a giant artificial neural network (ANN) that can have trillions of parameters and perform accelerated self-supervised learning from data searched from the Internet using an improved Common Crawl search engine. LLMs takes an input text and predicts the next token, much like natural language processing (NLP), taking an input text and repeatedly predicting the next token or word by various means, such as Hidden Markov Models (HMM) and recurrent neural networks (RNN) and their associated algorithms. Entirely new chapters on large language models (LLMs), ChatGPT, and quantum computing.

Название: Introduction to Python for Science and Engineering, 2nd Edition
Автор: David J. Pine
Издательство: CRC Press
Год: 2025
Страниц: 444
Язык: английский
Формат: pdf (true)
Размер: 23.4 MB

Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed. Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms. Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments. The aim of the second edition remains the same as the first: to provide science and engineering students a practical introduction to technical programming in Python. This new edition adds nearly 100 pages of new material. All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead.