# From an implementation point of view, what are the main differences between an RNN and a CNN?

I understand that in general an RNN is good for time series data and a CNN image data, and have noticed many blogs explaining the fundamental differences in the models.

As a beginner in machine learning and coding, I would like to know from the code perspective, what the differences between an RNN and CNN are in a more practical way.

For instance, I think most CNNs dealing with image data use Conv1D or Conv2D and MaxPooling2D layers and require reshaping input data with code looks something like this Input(shape=(64, 64, 1)).

What are some other things that distinguish CNNs from RNNs from a coding perspective?