This book presents neural networks from a theoretical viewpoint with practical applications. Unlike other books, which focus on a single architecture or view neural networks primarily through a machine learning prism, this book provides a comprehensive view of neural networks from its roots in neuroscience to recent work on both connectivity theory and statistical classification theory. Additionally, it describes a variety of neural network architectures under a unifying theory, allowing readers to better comprehend the variety of neural network algorithms.
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