Python for Deep Learning - Build Neural Networks in Python - Fully Connected Layer

The video tutorial explains the process of feature extraction in Convolutional Neural Networks (CNNs) using convolution and pooling layers. It describes how these layers detect features like edges and facial features in images. The tutorial then covers the integration of fully connected layers, which are similar to those in Artificial Neural Networks (ANNs), and explains the flattening process to convert 2D outputs into 1D vectors for classification. Finally, it provides an overview of the complete CNN process and transitions to the next lecture.

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