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 Название: Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure
Автор: Kristen Kehrer, Caleb Kaiser
Издательство: Wiley
Год: 2024
Страниц: 237
Язык: английский
Формат: True/Retail PDF, True EPUB
Размер: 10.75 MB
A much-needed guide to implementing new technology in workspaces. From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), Machine Learning, and Data Science. This groundbreaking book will change the way that you view the pipeline of Data Science. The authors provide an introduction to modern Machine Learning, showing you how it can be viewed as a holistic, end-to-end system?not just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn't been codified yet, enabling you to forge the future using emerging best practices. We intend this book to be something you can read all the way through. This is not an index of methods or a comprehensive book on Machine Learning. Our aim is to cover the challenges associated with modern-day Machine Learning with a particular focus on data versioning, experiment tracking, post-production model monitoring, and deployment to equip you with the code and examples to start leveraging best practices immediately. This book is indispensable for data professionals and business leaders looking to understand LLMs and the entire Data Science pipeline. | |
Разместил: Ingvar16 8-01-2025, 07:26 | Комментарии: 0 | Подробнее
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 Название: Graph Neural Network Methods and Applications in Scene Understanding
Автор: Weibin Liu, Huaqing Hao, Hui Wang, Zhiyuan Zou, Weiwei Xing
Издательство: Springer
Год: 2024
Страниц: 231
Язык: английский
Формат: pdf (true), epub
Размер: 56.0 MB
The book focuses on graph neural network methods and applications for scene understanding. Graph Neural Network is an important method for graph-structured data processing, which has strong capability of graph data learning and structural feature extraction. Scene understanding is one of the research focuses in Computer Vision and image processing, which realizes semantic segmentation and object recognition of image or video. In this book, the algorithm, system design and performance evaluation of scene understanding based on graph neural networks (GNNs) have been studied. First, the book elaborates the background and basic concepts of graph neural network and scene understanding, then introduces the operation mechanism and key methodological foundations of graph neural network. The book then comprehensively explores the implementation and architectural design of graph neural networks for scene understanding tasks, including scene parsing, human parsing, and video object segmentation. | |
Разместил: Ingvar16 8-01-2025, 04:01 | Комментарии: 0 | Подробнее
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 Название: AI Value Creators: Beyond the Generative AI User Mindset (Early Release)
Автор: Rob Thomas, Paul Zikopoulos, Kate Soule, Dario Gil
Издательство: O’Reilly Media, Inc.
Год: 2025-01-07
Страниц: 150
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB
We've arrived in a new era—GenAI is reshaping industries and decision-making processes across the board. As a result, understanding its potential and pitfalls has become crucial. But in order to stay ahead of the curve, you'll need to develop fresh perspectives on leveraging AI beyond mere technical know-how. Geared toward business leaders and tech professionals alike, this book demystifies the strategic integration of AI into business practices, ensuring you're equipped not just to participate but to lead in this new landscape. This insightful guide by industry leaders Rob Thomas, Paul Zikopoulos, Kate Soule, and Dario Gil goes beyond the basics, offering real-life success stories and learned lessons to provide a blueprint for meaningful AI engagement. Whether you're a novice or a seasoned expert, you'll come away with an enhanced understanding of GenAI. | |
Разместил: Ingvar16 7-01-2025, 22:29 | Комментарии: 0 | Подробнее
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 Название: Java: Learn Java Programming From Beginner to Professional
Автор: Philip Jeff
Издательство: Independently published
Год: 2024
Страниц: 340
Язык: английский
Формат: epub
Размер: 12.0 MB
Java: Learn Java Programming From Beginner to Professional This is your ultimate companion on the journey to mastering Java. If you are stepping into the world of programming for the first time or are an experienced developer looking to sharpen your skills, this book offers a structured and comprehensive guide to becoming a proficient Java programmer. Inside this book, you'll find clear explanations of Java concepts, supplemented with practical examples that bring the theory to life. Each chapter is crafted to build your knowledge progressively, ensuring you understand the foundational principles before moving on to more advanced topics. But this isn't just a book to read—it's a book to do. Every chapter includes carefully designed exercises that challenge you to apply what you've learned, solidifying your understanding through hands-on practice. And to make sure you're on the right track, detailed solutions are provided, helping you to identify any mistakes and learn from them. | |
Разместил: Ingvar16 7-01-2025, 20:46 | Комментарии: 0 | Подробнее
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 Название: AI in Disease Detection: Advancements and Applications
Автор: Rajesh Singh, Anita Gehlot, Navjot Rathour, Shaik Vaseem Akram
Издательство: Wiley-IEEE Press
Год: 2025
Страниц: 395
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB
Comprehensive resource encompassing recent developments, current use cases, and future opportunities for Artificial Intelligence (AI) in disease detection. AI in Disease Detection discusses the integration of Artificial Intelligence to revolutionize disease detection approaches, with case studies of AI in disease detection as well as insight into the opportunities and challenges of AI in healthcare as a whole. The book explores a wide range of individual AI components such as Computer Vision, natural language processing (NLP), and Machine Learning as well as the development and implementation of AI systems for efficient practices in data collection, model training, and clinical validation. Delivering excellent coverage of the subject, AI in Disease Detection is an essential up-to-date reference for students, healthcare professionals, academics, and practitioners seeking to understand the possible applications of AI in disease detection and stay on the cutting edge of the most recent breakthroughs in the field. | |
Разместил: Ingvar16 7-01-2025, 20:01 | Комментарии: 0 | Подробнее
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 Название: Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing
Автор: Abdul Rahman, Christopher Redino, Dhruv Nandakumar, Tyler Cody, Sachin Shetty, Dan Radke
Издательство: Wiley-IEEE Press
Год: 2025
Страниц: 277
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB
A comprehensive and up-to-date application of Reinforcement Learning concepts to offensive and defensive cybersecurity. In Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing, a team of distinguished researchers delivers an incisive and practical discussion of Reinforcement Learning (RL) in cybersecurity that combines intelligence preparation for battle (IPB) concepts with multi-agent techniques. The authors explain how to conduct path analyses within networks, how to use sensor placement to increase the visibility of adversarial tactics and increase cyber defender efficacy, and how to improve your organization’s cyber posture with RL and illuminate the most probable adversarial attack paths in your networks. Perfect for practitioners working in cybersecurity, including cyber defenders and planners, network administrators, and information security professionals, Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing will also benefit Computer Science researchers. | |
Разместил: Ingvar16 7-01-2025, 19:03 | Комментарии: 0 | Подробнее
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Название: Python для начинающих. Учимся программировать с помощью мини-игр и загадок
Автор: Юэнс-Кларк Кен
Издательство: Феникс
Год: 2025
Формат: PDF
Страниц: 548
Размер: 35 Mb
Язык: Русский
В книге "Python для начинающих" читатели найдут задания, позволяющие изучить этот язык программирования через решение увлекательных головоломок и создание игр. Каждая глава предлагает новую программу: от создания паролей до генерации шекспировских оскорблений. Издание подойдет для читателей с нулевым или начальным опытом в программировании, а также для тех, кто уже имеет опыт, но хочет изучить новый язык.
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Разместил: Chipa 7-01-2025, 11:29 | Комментарии: 0 | Подробнее
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 Название: Beyond Effective Go: Part 2 - Striving for High-Quality Code
Автор: Corey Scott
Издательство: Corey S. Scott
Год: 2024
Страниц: 337
Язык: английский
Формат: pdf, epub
Размер: 10.19 MB
Discover the unique secrets to writing high-quality code efficiently and effectively and dramatically improve your development productivity. Building on the success of Beyond Effective Go—Part 1: Achieving High-Performance Code, Corey shares wisdom and practical approaches to software engineering, software design, and code UX that will set you on the path to success. This series doesn’t waste time on the basics but dives straight into the solutions for the everyday challenges that professional programmers face. With clear explanations and real-world examples, you'll gain the skills to build performant, maintainable, and testable applications in Go efficiently and effectively. Unlike many programming books, Beyond Effective Go focuses on the programmer and the code. Whether you're building large-scale backend services or convenient automation tools, the book will help you write maintainable, high-quality code that meets the needs of your users, programmers, and your business. | |
Разместил: Ingvar16 7-01-2025, 04:42 | Комментарии: 0 | Подробнее
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 Название: Graph Learning Techniques
Автор: Baoling Shan, Xin Yuan, Wei Ni, Ren Ping Liu, Eryk Dutkiewicz
Издательство: CRC Press
Год: 2025
Страниц: 186
Язык: английский
Формат: pdf (true), epub
Размер: 23.4 MB
This comprehensive guide addresses key challenges at the intersection of Data Science, Graph Learning, and privacy preservation. It begins with foundational graph theory, covering essential definitions, concepts, and various types of graphs. The book bridges the gap between theory and application, equipping readers with the skills to translate theoretical knowledge into actionable solutions for complex problems. Graphs serve as a widely recognized representation of the network structure of interconnected data. They appear in various application domains, including social systems, ecosystems, biological networks, knowledge graphs, and information systems. As Artificial Intelligence technologies continue to advance, Graph Learning (i.e., Machine Learning applied to graphs) is attracting increasing interest from both researchers and practitioners. This approach has proven effective for numerous tasks, such as classification, link prediction, and matching, by utilizing Machine Learning algorithms to extract pertinent features from graphs. This resource is a valuable reference for advance undergraduate and postgraduate students in courses related to Network Analysis, Privacy and Security in Data Analytics, and Graph Theory and Applications in Healthcare. | |
Разместил: Ingvar16 7-01-2025, 02:12 | Комментарии: 0 | Подробнее
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 Название: Designing Distributed Systems: Patterns and Paradigms for Scalable, Reliable Systems Using Kubernetes, 2nd Edition
Автор: Brendan Burns
Издательство: O’Reilly Media, Inc.
Год: 2025
Страниц: 220
Язык: английский
Формат: True PDF, True EPUB
Размер: 10.1 MB
Every distributed system strives for reliability, performance, and quality, but building such a system is hard. Establishing a set of design patterns enables software developers and system architects to use a common language to describe their systems and learn from the patterns and practices developed by others. The popularity of containers and Kubernetes paves the way for core distributed system patterns and reusable containerized components. This practical guide presents a collection of repeatable, generic patterns to help guide the systems you build using common patterns and practices drawn from some of the highest performing distributed systems in use today. These common patterns make the systems you build far more approachable and efficient, even if you've never built a distributed system before. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system. | |
Разместил: Ingvar16 6-01-2025, 21:58 | Комментарии: 0 | Подробнее
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