BOOKS - Deep Learning Demystified A Step-by-Step Introduction to Neural Networks
Deep Learning Demystified A Step-by-Step Introduction to Neural Networks - Kilho Shin 2024 EPUB Independently published BOOKS
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Deep Learning Demystified A Step-by-Step Introduction to Neural Networks
Author: Kilho Shin
Year: 2024
Format: EPUB
File size: 11.6 MB
Language: ENG



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Deep Learning Demystified A StepbyStep Introduction to Neural Networks The book "Deep Learning Demystified" by Rajesh Pandey is an excellent resource for anyone looking to gain a deeper understanding of neural networks and their applications in deep learning. The author provides a comprehensive introduction to the subject, making it accessible even for those without prior experience in machine learning or programming. The book covers the fundamental concepts of deep learning, including the history of its development, the basics of neural networks, and the various architectures used in deep learning models. It also delves into more advanced topics such as convolutional neural networks, recurrent neural networks, and transfer learning. The book begins with an overview of the evolution of technology and how it has impacted society throughout history. The author highlights the importance of understanding this process in order to appreciate the significance of deep learning in modern knowledge. He argues that developing a personal paradigm for perceiving technological advancements is crucial for humanity's survival and the unification of people in a warring state.
Deep arning Demystified A StepbyStep Введение в нейронные сети Книга Раджеша Пандея «Deep arning Demystified» является отличным ресурсом для всех, кто хочет глубже понять нейронные сети и их приложения в глубоком обучении. Автор предоставляет всестороннее введение в предмет, делая его доступным даже для тех, кто не имеет предшествующего опыта в машинном обучении или программировании. Книга охватывает фундаментальные концепции глубокого обучения, включая историю его развития, основы нейронных сетей и различные архитектуры, используемые в моделях глубокого обучения. Он также углубляется в более продвинутые темы, такие как сверточные нейронные сети, рекуррентные нейронные сети и передача обучения. Книга начинается с обзора эволюции технологий и того, как они влияли на общество на протяжении всей истории. Автор подчеркивает важность понимания этого процесса, чтобы оценить значение глубокого обучения в современных знаниях. Он утверждает, что разработка личной парадигмы восприятия технологических достижений имеет решающее значение для выживания человечества и объединения людей в воюющем государстве.
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