BOOKS - Demystifying Artificial Intelligence Symbolic, Data-Driven, Statistical and E...
Demystifying Artificial Intelligence Symbolic, Data-Driven, Statistical and Ethical AI - Emmanuel Gillain 2024 PDF | EPUB De Gruyter BOOKS
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Demystifying Artificial Intelligence Symbolic, Data-Driven, Statistical and Ethical AI
Author: Emmanuel Gillain
Year: 2024
Pages: 476
Format: PDF | EPUB
File size: 34.1 MB
Language: ENG



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Demystifying Artificial Intelligence Symbolic DataDriven Statistical and Ethical AI by Dr. Suresh Venkatasubramanian is a groundbreaking book that sheds light on the complex world of artificial intelligence (AI), providing readers with a comprehensive understanding of the field's various aspects. The author, a renowned expert in the field, offers a unique perspective on AI, emphasizing the importance of symbolic data-driven approaches, statistical methods, and ethical considerations. Through this book, readers will gain a deeper appreciation for the intricacies of AI and its potential to revolutionize numerous industries and aspects of society. The book begins by exploring the history and evolution of AI, tracing its development from ancient times to the present day. This historical context sets the stage for an in-depth examination of the fundamental principles of AI, including machine learning, deep learning, and neural networks. Readers will learn how these techniques are used in real-world applications, such as image recognition, natural language processing, and predictive analytics.
Demystifying Artificial Intelligence Symbolic DataDriven Statistical and Ethical AI by Dr. Suresh Venkatasubramanian - это новаторская книга, которая проливает свет на сложный мир искусственного интеллекта (ИИ), предоставляя читателям всестороннее понимание различных аспектов этой области. Автор, известный эксперт в этой области, предлагает уникальный взгляд на ИИ, подчеркивая важность подходов, основанных на символических данных, статистических методов и этических соображений. Благодаря этой книге читатели получат более глубокую оценку тонкостей ИИ и его потенциала революционизировать многочисленные отрасли и аспекты жизни общества. Книга начинается с изучения истории и эволюции ИИ, прослеживая его развитие от древнейших времен до наших дней. Этот исторический контекст закладывает основу для углубленного изучения фундаментальных принципов ИИ, включая машинное обучение, глубокое обучение и нейронные сети. Читатели узнают, как эти методы используются в реальных приложениях, таких как распознавание изображений, обработка естественного языка и прогнозная аналитика.
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