I\'m just beginning my ML journey and have done a few tutorials. One thing that\'s not clear (to me) is how the \'filter\' parameter is determined for Keras Conv2D.
Mos
Number of filters is chosen based complexity of task. More complex tasks require more filters. And usually number of filters grows after every layer (eg 128 -> 256 -> 512
). First layers (with lower number of filters) catch few of some simple features of images (edges, color tone, etc) and next layers are trying to obtain more complex features based on simple ones.
There is nice course from Stanford to give you intuition and understanding of CNN.