Convolutional Neural Networks

1. Convolutional Neural Networks (CNNs) are a powerful tool for deep learning, allowing us to extract features from images, text, and other data. 2. In CNNs, convolutional layers are used to extract features from the input data. This is done by convolving the input data with a set of filters or kernels. 3. The output of the convolutional layer is fed to a fully connected layer, which is used to classify the data into different classes. 4. By using CNNs, we can achieve state-of-the-art results in image classification, object detection, and language understanding tasks. 5. The key to designing CNNs is understanding how to design the convolutional layers, which can be used to identify patterns in the input data. 6. With the help of CNNs, we can learn complex models from large datasets, allowing us to build powerful AI systems.