exData = pd.read_csv('AP11.csv',delimiter=';',float_precision=None) pd.set_option('display.max_colwidth', None ) x = exData.loc[:,['A','B']] y = exData.loc[:,['C']] x=x.astype('int64') y=y.astype('int64') opt = Adam(lr=0.001, decay=1e-6) model = keras.Sequential([ keras.layers.Dense(2, input_dim=2, activation=keras.activations.sigmoid ), keras.layers.Dense(1, activation=keras.activations.relu ), ]) model.compile(optimizer=opt, loss="categorical_crossentropy", metrics=model.compile(optimizer=opt, loss="categorical_crossentropy", metrics=['accuracy'])) model.fit(x,y, batch_size=64, epochs=100)
Hello, I want to feed my data to keras as int64 and i want keras to process it as int64 and outputs it as int64. i don't want any float64 to be involved in the process. float64 is not precise at all for my application. i think you might notice that my code is not so good because i didn't program machine learning before so please do correct me to improve my code if needed.
https://stackoverflow.com/questions/65756943/input-int64-to-keras-and-process-data-using-int64-only January 17, 2021 at 11:05AM
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