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 Название: Biomedical Imaging: Advances in Artificial Intelligence and Machine Learning
Автор: Ankur Gogoi, Nirmal Mazumder
Издательство: Springer
Год: 2024
Страниц: 359
Язык: английский
Формат: pdf (true), epub
Размер: 61.0 MB
This book presents the rapidly developing field of Artificial Intelligence (AI) and Machine Learning and its application in biomedical imaging. As is known, starting from the diagnosis of fractures by using X-rays to understanding the complex structure and function of the brain, biomedical imaging has contributed immensely toward the development of precision diagnosis and treatment strategies for numerous diseases. While continuous evolution in imaging technologies have enabled the acquisition of images having resolution and contrast far better than ever, it significantly increased the volume of data associated with each image scan—making it increasingly difficult for experts to analyze and interpret. In this context, the application of Artificial Intelligence (AI) and Machine Learning (ML) tools has become one of the most exciting frontlines of contemporary research in biomedical imaging due to their capability to extract minute traces of various disease signatures from large and complicated datasets and providing clear insight into the potential abnormalities with excellent accuracy, sensitivity, and specificity. The book covers a range of topics, from the fundamentals of AI, ML, and Deep Learning (DL) to the latest applications of these techniques in the analysis and interpretation of various medical imaging modalities. | |
Разместил: Ingvar16 28-09-2024, 02:51 | Комментарии: 0 | Подробнее
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 Название: Data Engineering for Machine Learning Pipelines: From Python Libraries to ML Pipelines and Cloud Platforms
Автор: Pavan Kumar Narayanan
Издательство: Apress
Год: 2024
Страниц: 631
Язык: английский
Формат: pdf
Размер: 33.0 MB
This book covers modern data engineering functions and important Python libraries, to help you develop state-of-the-art ML pipelines and integration code. The book begins by explaining data analytics and transformation, delving into the Pandas library, its capabilities, and nuances. It then explores emerging libraries such as Polars and CuDF, providing insights into GPU-based computing and cutting-edge data manipulation techniques. The text discusses the importance of data validation in engineering processes, introducing tools such as Great Expectations and Pandera to ensure data quality and reliability. The book delves into API design and development, with a specific focus on leveraging the power of FastAPI. It covers authentication, authorization, and real-world applications, enabling you to construct efficient and secure APIs using FastAPI. Also explored is concurrency in data engineering, examining Dask's capabilities from basic setup to crafting advanced machine learning pipelines. The book includes development and delivery of data engineering pipelines using leading cloud platforms such as AWS, Google Cloud, and Microsoft Azure. The concluding chapters concentrate on real-time and streaming data engineering pipelines, emphasizing Apache Kafka and workflow orchestration in data engineering. Workflow tools such as Airflow and Prefect are introduced to seamlessly manage and automate complex data workflows. What sets this book apart is its blend of theoretical knowledge and practical application, a structured path from basic to advanced concepts, and insights into using state-of-the-art tools. For data analysts, data engineers, data scientists, Machine Learning engineers, and MLOps specialists. | |
Разместил: Ingvar16 27-09-2024, 20:03 | Комментарии: 0 | Подробнее
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 Название: Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib, 3rd Edition
Автор: Robert Johansson
Издательство: Apress
Год: 2024
Страниц: 485
Язык: английский
Формат: pdf
Размер: 24.5 MB
Learn how to leverage the scientific computing and data analysis capabilities of Python, its standard library, and popular open-source numerical Python packages like NumPy, SymPy, SciPy, Matplotlib, and more. This book demonstrates how to work with mathematical modeling and solve problems with numerical, symbolic, and visualization techniques. It explores applications in science, engineering, data analytics, and more. Numerical Python, Third Edition, presents many case study examples of applications in fundamental scientific computing disciplines, as well as in Data Science and statistics. This fully revised edition, updated for each library's latest version, demonstrates Python's power for rapid development and exploratory computing due to its simple and high-level syntax and many powerful libraries and tools for computation and data analysis. After reading this book, readers will be familiar with many computing techniques, including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling, and Machine Learning. For developers who want to understand how to use Python and its ecosystem of libraries for scientific computing and data analysis. | |
Разместил: Ingvar16 27-09-2024, 19:32 | Комментарии: 0 | Подробнее
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 Название: Deep Learning for 3D Vision: Algorithms and Applications
Автор: Xiaoli Li, Xulei Yang, Hao Su
Издательство: World Scientific Publishing
Год: 2024
Страниц: 493
Язык: английский
Формат: pdf (true)
Размер: 20.9 MB
3D Deep Learning is a rapidly evolving field that has the potential to transform various industries. This book provides a comprehensive overview of the current state-of-the-art in 3D Deep Learning, covering a wide range of research topics and applications. It collates the most recent research advances in 3D Deep Learning, including algorithms and applications, with a focus on efficient methods to tackle the key technical challenges in current 3D Deep Learning research and adoption, therefore making 3D Deep Learning more practical and feasible for real-world applications. For any AI-enabled agent to accomplish its task, visual understanding or perception is the first step towards interacting with the three-dimensional (3D) world. Due to its inherent limitations, visual understanding techniques based solely on two-dimensional (2D) images may be inadequate for real-world applications. This calls for 3D Deep Learning techniques that operate on 3D data, which enables a direct visual understanding of the 3D world. In recent years, 3D Deep Learning has been attracting increasing attention. As we live in a 3D world, 3D Deep Learning is a natural way to perceive and understand our environment, enabling emerging and new industrial applications, such as autonomous driving, robot perception, medical imaging, and scientific simulations, and many more. In the context of 3D Deep Learning, deep neural networks have been adapted and extended to work with 3D data, including point clouds, meshes, and volumetric data. This has led to significant progress in tasks, such as 3D object detection and segmentation, point cloud classification, and 3D reconstruction. | |
Разместил: Ingvar16 27-09-2024, 12:49 | Комментарии: 0 | Подробнее
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 Название: Applied OSS Reliability Assessment Modeling, AI and Tools: Mathematics and AI for OSS Reliability Assessment
Автор: Yoshinobu Tamura, Shigeru Yamada
Издательство: Springer
Год: 2024
Страниц: 191
Язык: английский
Формат: pdf (true), epub
Размер: 32.2 MB
This textbook introduces the theory and application of open source software (OSS) reliability. The measurement and management of open source software are essential to produce and maintain quality and reliable systems while using open source software. This book describes the latest methods for the reliability assessment of open source software. This book will serve as a textbook and reference book for graduate students and researchers in reliability for open source software, modeling, and Deep Learning. Several latest methods of reliability assessment for open source software are introduced. We aim to present the state-of-the-art of open source software reliability measurement and assessment based on the stochastic modeling and Deep Learning approaches. For example, stochastic differential equation models, two dimensional stochastic differential equation models, Deep Learning methods, tools are presented. The book contains exercises to aid learning and is useful for graduate students and researchers. | |
Разместил: Ingvar16 27-09-2024, 11:01 | Комментарии: 0 | Подробнее
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 Название: Automate ChatGPT Prompts for Data Science with Python: Enhanced Coding for the Modern Python Developer
Автор: Pol Camarillo, Thomas Carroll
Издательство: Independently published
Год: 2024
Страниц: 100
Язык: английский
Формат: pdf, epub
Размер: 17.2 MB
Python is a global programming language used by equally data engineers & data scientists, and it is also the most popular. Python is loved by all the Data Scientists I've talked to and many of my friends since it can automate all the mundane operational work that data engineers must perform. Here what you'll learn after downloading this book: - ChatGPT Prompts for Data Science (Tried, Tested, and Rated); - Write Python; - Optimize Code; - Format Code; - Translate Code; - Troubleshoot Problem; - Write SQL; - Write Other Code; - Miscallaneous, And more... This Book Is Perfect For: - Total beginners with zero programming experience; - Returning professionals who haven’t written code in years; - Seasoned professionals looking for a fast, simple, crash course in Python. | |
Разместил: Ingvar16 27-09-2024, 02:14 | Комментарии: 0 | Подробнее
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 Название: Foundation Mathematics for Computer Science: A Visual Approach, 4th Edition
Автор: John Vince
Издательство: Springer
Год: 2024
Страниц: 646
Язык: английский
Формат: pdf (true), epub
Размер: 76.5 MB
In this book, John Vince has reviewed and edited the third edition and added chapters on statistics, Georg Riemann’s hypothesis, eigen vectors, curves, analytic geometry and Fourier analysis. These subjects complement the existing chapters on visual mathematics, numbers, algebra, logic, combinatorics, probability, modular arithmetic, trigonometry, coordinate systems, determinants, vectors, complex numbers, matrices, geometric matrix transforms, differential and integral calculus. During this journey, the author touches upon more esoteric topics such as quaternions, octonions, Grassmann algebra, barycentric coordinates, transfinite sets and prime numbers. John Vince describes a range of mathematical topics that provide a solid foundation for an undergraduate course in Computer Science, starting with a review of number systems and their relevance to digital computers and finishing with calculating area and volume using calculus. Readers will find that the author’s visual approach should greatly improve their understanding as to why certain mathematical structures exist, together with how they are used in real-world applications. This book includes new, full-colour illustrations to clarify the mathematical descriptions, and in some cases, equations are also coloured to reveal vital algebraic patterns. The numerous worked examples will help consolidate the understanding of abstract mathematical concepts. Whether you intend to pursue a career in programming, scientific visualization, Artificial Intelligence, systems design or real-time computing, you should find the author’s literary style refreshingly lucid and engaging and prepare you for more advanced texts. | |
Разместил: Ingvar16 27-09-2024, 01:31 | Комментарии: 0 | Подробнее
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 Название: Foundations and Opportunities of Biometrics: An Introduction to Technology, Applications, and Responsibilities
Автор: Dario Salice, Jennifer Salice
Издательство: Apress
Год: 2024
Страниц: 169
Язык: английский
Формат: pdf, epub (true), azw3, mobi
Размер: 10.1 MB
Biometrics are used in many situations of our daily lives, but we still don’t fully understand the way they work and what potential lies behind them. This book covers a fascinating and broad area that impacts everyone, not only companies involved in deep-tech. Over the past decades, biometrics have made their way into our daily lives after being first limited to science fiction and later expensive high-tech applications. With the widespread use of smartphones and other technological gadgets we interact with on a daily basis, the ability to collect and use biometric signals has become ubiquitous. Your phone scans your face to give you access. Your laptop uses your fingerprint. Your smart speaker recognizes your voices and answers questions based on which user asked them. These are just a few of the ways biometric data is used in our everyday lives. This book provides a comprehensive overview of the type of biometric signals that are being used, how they are implemented, and what their limitations are. With technology being more relevant in all aspects of life, it’s more important for people who make decisions in their business to understand the opportunities and limitations of biometric use. This book will guide the readerthrough the history of biometric technology, including initial applications of the technology, and reflect on how pop culture like science fiction media has influenced the way we look at biometrics and shaped our expectations and fears. It also covers real-world applications and how they work. This book provides foundational information that will help readers understand how they can use biometrics in their everyday life and assess their ability to disrupt existing business processes and models. | |
Разместил: Ingvar16 26-09-2024, 19:07 | Комментарии: 0 | Подробнее
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 Название: AI Revolution: Mastering AI for Personal and Organizational Growth
Автор: Tero Ojanperä
Издательство: River Publishers
Год: 2024
Страниц: 181
Язык: английский
Формат: pdf (true), epub
Размер: 56.0 MB
“The AI Revolution” is a practical guide to using new AI tools, such as ChatGPT, DALLE and Midjourney. Learn how to multiply your productivity by guiding or prompting AI in various ways. The book also introduces Microsoft Copilot, Google Bard, and Adobe Photoshop Generative Fill, among other new applications. ChatGPT reached a hundred million users in just two months after its release, faster than any other application before. This marked the advent of the generative AI era. Generative AI models generate text, images, music, videos, and even 3D models in ways previously thought impossible for machines. The book explains in an understandable manner how these AI models work. The book provides examples of how AI increases productivity, which professions are changing or disappearing, and how job markets will evolve in the coming years. With this book, you'll learn to recognize the opportunities and risks AI offers. Understand what this change demands from individuals and companies and what strategic skills are required. The book also covers legal questions caused by generative AI, like copyrights, data protection, and AI regulation. It also ponders societal impacts. AI produces content, thus influencing language, culture, and even worldviews. Therefore, it’s crucial to understand by whom and how AI is trained. The AI revolution started by ChatGPT is just the beginning. This handbook is for you if you want to keep up with the rapid development of AI. “The AI Revolution” is a practical guide to using new AI tools, such as ChatGPT. Generative AI models produce text, images, music, videos, and even 3D models in a way that was previously believed to be impossible for machines. GitHub Copilot, based on OpenAI’s generative AI model Codex, significantly improved programmers’ performance. According to the study, programmers who had access to Copilot completed tasks over 50% faster than those who did not use the tool. Less experienced programmers, older programmers, and those who program for several hours a day benefited the most from the tool. | |
Разместил: Ingvar16 26-09-2024, 17:33 | Комментарии: 0 | Подробнее
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 Название: Artificial Intelligence in Workplace Health and Safety: Data-Driven Technologies, Tools and Techniques
Автор: Mohammad Yazdi
Издательство: CRC Press
Серия: Intelligent Data-Driven Systems and Artificial Intelligence
Год: 2025
Страниц: 127
Язык: английский
Формат: pdf (true), epub
Размер: 16.3 MB
In today's dynamic workplace environment, ensuring the safety and well-being of employees has never been more critical. This book explores cutting-edge technologies intersecting with workplace safety to deliver effective and practical results. Artificial Intelligence in Workplace Health and Safety: Data-Driven Technologies, Tools and Techniques offers a comprehensive roadmap for professionals, researchers, and practitioners in work health and safety (WHS), revolutionizing traditional approaches through the integration of data-driven methodologies and Artificial Intelligence (AI). Covering the foundations and practical applications of data-driven WHS and historical perspectives to current regulatory frameworks, it investigates the key concepts of data collection, management, and integration. Through real-world case studies and examples, readers can discover how AI technologies such as Machine Learning, computer vision, and natural language processing (NLP) are reshaping WHS practices, mitigating risks, and optimizing safety measures. The reader will learn applications of AI and data-driven methodologies in their workplace settings to improve safety. With its practical insights, real-world examples, and progressive approach, this title ensures that readers are not just prepared for the future of WHS but empowered to shape it for better. Machine Learning (ML): Machine learning, a core subset of AI, involves algorithms that enable systems to learn from and interpret data without explicit programming. In WHS, ML can be utilized to analyze vast amounts of incident data, workplace audits, and risk assessments. With the recognizing patterns and predicting potential hazards, ML aids in proactive safety management, reducing the likelihood of accidents before they occur. | |
Разместил: Ingvar16 26-09-2024, 16:42 | Комментарии: 0 | Подробнее
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