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.

Название: Server-Driven Web Apps with htmx
Автор: R. Mark Volkmann
Издательство: Pragmatic Bookshelf
Год: August 2024 (Book version: P1.0)
Страниц: 182
Язык: английский
Формат: pdf (true), epub, mobi
Размер: 15.2 MB

htmx is a library that adds logic and server interaction to HTML; you get the effect of using a front-end SPA framework without writing front-end code. Use any server-side programming language and framework to build server applications with endpoints that simply return snippets of HTML. Dynamically update portions of the current web page from HTTP responses. Add interactivity with jаvascript and libraries such Alpine and _hyperscript. Make your apps more secure by escaping user-supplied content and specifying a Content Security Policy. Go beyond basic HTTP requests with WebSockets and server-sent events. The htmx jаvascript library gives you a new way to craft web applications. The htmx approach differs significantly from that of the currently popular single-page application (SPA) frameworks; rather than write a bunch of jаvascript, you simply annotate HTML elements before you send them to the browser. The resulting code is easier to understand and modify, and because it downloads less to the browser and doesn't need JSON creation and parsing, you'll find it performs better, too. The htmx library is quite small—less than 17KB minified and compressed. Pages load faster due to downloading less jаvascript code than when using typical SPA frameworks. You can see these improvements with app metrics such as First Contentful Paint and Time to Interactive. Htmx applications also provide faster server interactions because the time spent generating and parsing JSON is eliminated.

Название: Synergy of AI and Fintech in the Digital Gig Economy
Автор: Alex Khang, Babasaheb Jadhav, Vugar Abdullayev Hajimahmud, Ipseeta Satpathy
Издательство: CRC Press
Год: 2025
Страниц: 442
Язык: английский
Формат: pdf (true)
Размер: 19.8 MB

The convergence of Artificial Intelligence (AI) and Financial Technology (Fintech) has ushered in a new era of innovation in the finance ecosystem, particularly within the context of the digital gig economy. This emerging trend has created a unique set of challenges and opportunities, which AI and Fintech are poised to address. This book explores how the convergence of these cutting-edge technologies is reshaping the financial landscape, especially related to the way people work and earn in the gig economy, and examines the rise of the digital gig economy and its impact on the traditional workforce. Synergy of AI and Fintech in the Digital Gig Economy presents the key advancements in AI and Fintech, how they are disrupting traditional financial systems, and how AI-powered tools and platforms are streamlining financial processes, enhancing decision-making, and providing personalized services to individuals and businesses. AI refers to the simulation of human intelligence in machines, enabling them to perform tasks typically requiring human intelligence, such as learning, reasoning, problem‑solving, and decision‑making. AI systems use algorithms and large datasets to recognize patterns, make predictions, and improve their performance over time. ML is a subset of AI focused on the development of algorithms that enable machines to learn from and make predictions or decisions based on data. ML algorithms use statistical techniques to allow computers to improve their performance on a specific task through learning from data, without being explicitly programmed. ML is the core technology that drives many AI applications, as it provides systems the ability to adapt and improve with experience. In recent years, the integration of Artificial Intelligence (AI) and Machine Learning (ML) has emerged as a game‑changer in fintech. AI‑powered chatbots, robo‑advisors, and fraud detection systems have revolutionized customer service, investment management, and risk mitigation in the financial industry.

Название: The AI Playbook: Mastering the Rare Art of Machine Learning Deployment
Автор: Eric Siegel
Издательство: The MIT Press
Год: 2024
Страниц: 255
Язык: английский
Формат: pdf (true)
Размер: 10.4 MB

In his bestselling first book, Eric Siegel explained how Machine Learning works. Now, in The AI Playbook, he shows how to capitalize on it. This book presents a strategic and tactical playbook for launching Machine Learning, a six-­step discipline to run an ML project so that it successfully deploys. I call this practice bizML. The greatest tool is the hardest to use. Machine Learning is the world's most important general-purpose technology—but it's notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, Machine Learning initiatives routinely fail to deploy, never realizing value. What's missing? A specialized business practice suitable for wide adoption. In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering Machine Learning projects from conception to deployment. He illustrates the practice with stories of success and of failure, including revealing case studies from UPS, FICO, and prominent dot-coms. This disciplined approach serves both sides: It empowers business professionals, and it establishes a sorely needed strategic framework for data professionals. Beyond detailing the practice, this book also upskills business professionals—painlessly. It delivers a vital yet friendly dose of semi-technical background knowledge that all stakeholders need to lead or participate in Machine Learning projects, end to end. This puts business and data professionals on the same page so that they can collaborate deeply, jointly establishing precisely what Machine Learning is called upon to predict, how well it predicts, and how its predictions are acted upon to improve operations. These essentials make or break each initiative—getting them right paves the way for Machine Learning's value-driven deployment.