08_deeplearning_softmax

softmax

softmax regression

cost

numerical roundoff errors

model =  Sequential([
Dense(units=25,activation='sigmoid'),
Dense(units=15,activation='sigmoid'),
Dense(units=1,activation='sigmoid'),
])
from tensorflow.keras.losses import BinaryCrossentropy
model.compile(...,BinaryCrossentropy(from_logits=True))
model.fit(X,Y,epochs=100)
logit = model(X)
f_x = tf.nn.sigmoid(logit)

Multi-label Classification