Simple explanation of convolutional neural network | Deep Learning Tutorial 23 (Tensorflow & Python)

3-Second Blueprint (English)

1. Standard neural networks on raw pixel grids fail when digits shift, whereas CNNs apply sliding filters to detect local patterns.
2. Convolving learned feature-detector kernels across an image produces activation feature maps with spatial translation invariance.
3. Max and average pooling with configurable windows and strides reduce spatial dimensions, computation cost, and parameter overfitting.