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Neural Networks

Mohit Rathore edited this page May 12, 2018 · 13 revisions

Our workflow should be like that of Keras and not like the present one -

Here is the Sequential model:

from keras.models import Sequential

model = Sequential()

Stacking layers is as easy as .add():

from keras.layers import Dense

model.add(Dense(units=64, activation='relu', input_dim=100))
model.add(Dense(units=10, activation='softmax'))

Once your model looks good, configure its learning process with .compile():

model.compile(loss='categorical_crossentropy',
              optimizer='sgd',
              metrics=['accuracy'])

(taken from its readme)

http://keras.dhpit.com

https://github.com/dennybritz/nn-from-scratch/blob/master/nn-from-scratch.ipynb

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