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Explore the fundamental concepts of convolutional neural networks in this comprehensive tutorial led by Han Wang from the University of Edinburgh. Delve into the core principles and architecture of CNNs, understanding their applications in image processing and pattern recognition. Learn about key components such as convolutional layers, pooling operations, and activation functions. Gain insights into the training process, including backpropagation and optimization techniques specific to CNNs. Discover how these powerful deep learning models have revolutionized computer vision tasks and their potential applications in various fields. This tutorial, part of the "Theoretical and Practical Perspectives in Geophysical Fluid Dynamics" program at the International Centre for Theoretical Sciences, offers a solid foundation for both beginners and those looking to refresh their knowledge on convolutional neural networks.
