Data Science and Machine Learning (Theory and Projects) A to Z - Classical CNNs: AlexNet

The video introduces convolutional neural networks (CNNs), focusing on the historical context and significance of AlexNet, which won the 2012 ImageNet challenge. It compares the architectures of LeNet and AlexNet, highlighting their differences and similarities. LeNet is described with its use of average pooling and sigmoid activation, while AlexNet is noted for its deeper architecture, use of ReLU activation, and max pooling. The video emphasizes the shift from manually designed features to learned features in CNNs, marking a significant advancement in computer vision.

Who introduced the very first convolutional neural network for handwritten digit recognition?

What is the architecture of AlexNet in terms of layers?

What significant achievement did AlexNet accomplish in 2012?

How does the feature learning of AlexNet compare to manually designed features?

What are the main differences between the architectures of Lenet and AlexNet?

What type of pooling was used in Lenet compared to AlexNet?

What impact did AlexNet have on the field of convolutional neural networks?