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Hands-On Predictive Analytics with Python
book

Hands-On Predictive Analytics with Python

by Alvaro Fuentes
December 2018
Beginner to intermediate content levelBeginner to intermediate
330 pages
8h 32m
English
Packt Publishing
Content preview from Hands-On Predictive Analytics with Python

Using a validation set

Before implementing early stopping, let's see how easy it is in Keras to monitor a loss that is calculated in a validation set; here, we will build another neural network for the diamond prices dataset:

nn_reg2 = Sequential()n_hidden = 64# hidden layersnn_reg2.add(Dense(units=n_hidden, activation='relu', input_shape=(n_input,)))nn_reg2.add(Dense(units=n_hidden, activation='relu'))nn_reg2.add(Dense(units=n_hidden, activation='relu'))nn_reg2.add(Dense(units=n_hidden, activation='relu'))nn_reg2.add(Dense(units=n_hidden, activation='relu'))nn_reg2.add(Dense(units=n_hidden, activation='relu'))# output layernn_reg2.add(Dense(units=1, activation=None))nn_reg2.compile(loss='mean_squared_error', optimizer='adam', metrics=['mse', ...
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Publisher Resources

ISBN: 9781789138719Supplemental Content