TF1 C2W3 - Output shape of first convolution

why does the first convolution from the Inception architecture in C2_W3_Lab_1_transfer_learning.ipynb takes the shape from (150, 150, 3) to (74, 74, 32)?
Based on what we saw in previous weeks I was expecting the output to be (148, 148, 3)

What is the parameter that is making this convolution to act as convolution+maxdrop altogether?

Please inspect filters, strides and kernel_size attributes of the conv layer that interests you using pre_trained_model.get_layer(LAYER_NAME).

It seems like you’ve completed the 4th course in deep learning specialization. Do go back to the lectures and find out details on how output shapes are calculated based on the above hints.

What’s this term?

I meant ‘maxpooling’