Ans: A technique to reduce the information in an image while maintaining features
3. How do Convolutions improve image recognition?
Ans: They isolate features in images
4. After passing a 3×3 filter over a 28×28 image, how big will the output be?
Ans: 26×26
5. After max pooling a 26×26 image with a 2×2 filter, how big will the output be?
Ans: 13×13
6. Applying Convolutions on top of our Deep neural network will make training:
Ans: It depends on many factors. It might make your training faster or slower, and a poorly designed Convolutional layer may even be less efficient than a plain DNN!
