Step 1: Understand what a CNN is. A CNN (Convolutional Neural Network) is a type of neural network used for image processing and recognition.
Step 2: Learn about overfitting. Overfitting happens when a model learns the training data too well, including noise, and performs poorly on new data.
Step 3: Know what dropout does. Dropout is a technique that randomly turns off (sets to zero) a certain percentage of neurons during training.
Step 4: Realize the purpose of dropout. By turning off some neurons, dropout helps the model to not rely too much on any single neuron, which reduces overfitting.
Step 5: Remember that dropout is only used during training. When the model is being tested or used for predictions, all neurons are active.
