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Introduces the fundamentals of deep learning, covering neural networks, CNNs, special layers, weight initialization, data preprocessing, and regularization.
Introduces feed-forward networks, covering neural network structure, training, activation functions, and optimization, with applications in forecasting and finance.
Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.
