Which activation function is most commonly used after batch normalization?

Which method fits the tokenizer on the texts?

What will this code output?

Which optimizer adapts learning rates for each parameter and often converges faster in noisy problems?

Given the following MLP model built using Keras:

What is the output shape of this model?

Which attribute correctly shows the shape of the extracted feature maps?

Why does the scaled version usually show higher accuracy?

Which expression completes the Xavier/Glorot initialization limit?

What value should replace the blank to match the number of features?

Insert the missing argument to complete the model based on MobileNetV2: