aditsanghvi94

Looks like there could be some differences when you shuffle the data in the SVC? set the random_state parameter for SVC = 1 as well in both the models ,...

This is what I did. ``` def f_nn(params): print ('Params testing: ', params) optimizer = Adam(10**params['lr']) # build model model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy']) ```