Deep Learning CNN Convolutional Neural Networks with Python - AlexNet

The video introduces convolutional neural networks (CNNs), focusing on AlexNet, a groundbreaking model that won the ImageNet challenge in 2012. It compares AlexNet with LeNet, highlighting differences in architecture, such as the use of ReLU activation and max pooling in AlexNet. The video emphasizes AlexNet's impact on the field, encouraging a shift from manually designed features to learned features.

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

What is the architecture of AlexNet and how many layers does it have?

In what year did AlexNet win the ImageNet large scale visual recognition challenge?

What are the main differences between Lenet and AlexNet in terms of architecture?

What activation function is used in AlexNet, and how does it differ from Lenet?

Describe the pooling methods used in Lenet and AlexNet.

How did AlexNet change the approach to feature learning in convolutional neural networks?