Run on Convolutions
Explore the construction and training of convolutional neural networks (CNNs) applied to the CIFAR-10 image dataset. Learn how CNNs preserve spatial information through convolutional layers, apply filters to detect features, and use batch normalization and dropout to enhance accuracy and reduce overfitting. This lesson helps you understand building effective CNN models and their advantages over fully connected networks in image recognition tasks.
We'll cover the following...
We'll cover the following...
CNN for CIFAR-10
A convolutional neural network for CIFAR-10 is:
In the code below, our Cifar-10 classifier undergoes training for 3 epochs, but to obtain better accuracy we must increase the number of epochs. The results of training the ...