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This groundbreaking book offers a comprehensive introduction to deep learning, covering its mathematical foundations, algorithms, and applications. It delves into various deep learning architectures, including convolutional neural networks, recurrent neural networks, and generative models. The book also explores practical aspects of deep learning, such as implementation, optimization, and hyperparameter tuning. It is considered a foundational text for understanding the principles and techniques of deep learning.
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