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This lecture covers the fundamentals of Convolutional Neural Networks (CNNs), explaining the structure and function of convolutional layers, pooling layers, and fully connected layers. It also delves into the concept of 2x2 filters, the process of max and average pooling, and the importance of weight sharing in CNNs.