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@amankharwal
Created Nov 24, 2020
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model = Sequential()
model.add(Conv2D(filters = 64, kernel_size = (3,3),padding = 'Same',activation ='relu', input_shape = (SIZE,SIZE,3)))
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Conv2D(filters = 128, kernel_size = (3,3),padding = 'Same',activation ='relu'))
model.add(Conv2D(filters = 128, kernel_size = (3,3),padding = 'Same',activation ='relu'))
model.add(Conv2D(filters = 128, kernel_size = (3,3),padding = 'Same',activation ='relu'))
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(Dense(64, activation='relu'))
model.add(Dropout(rate=0.5))
model.add(Dense(5, activation = "softmax"))
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