I am using keras to build a cnn model for signal classification. What is the best way in keras for hyper parameter tuning and selection for the number of strides,and number filters.
Selecting number of strides and filters in CNN (Keras)
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Welcome to main question of deep learning. There is no valid, single solution which fits to all problems. There are some patterns though, like starting with few filters in early layers and increase filter count while reducing the sizes. For you, the best would be to start reading existing architectures like Inception, VGG, Resnet, etc. to understand why and how they implemented their network. Then, by following / inventing your own network, you can try for better results.