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Understanding Deep Learning offers a comprehensive introduction to deep learning, providing a conceptual understanding of its principles and mathematical foundations. This book explores neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and other advanced techniques used in image recognition, natural language processing, and other applications. It equips readers with the knowledge to design, implement, and adapt deep learning models for solving complex problems, delving into optimization algorithms, regularization methods, and evaluation metrics. The text balances theoretical concepts with practical examples, making it accessible to students, researchers, and practitioners.
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Binding: Softcover
Condition: Pre-owned – Never used
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