Fitting the model
You're at the most fun part. You'll now fit the model. Recall that the data to be used as predictive features is loaded in a NumPy array called predictors and the data to be predicted is stored in a NumPy array called target. Your model is pre-written and it has been compiled with the code from the previous exercise.
Latihan ini adalah bagian dari kursus
Introduction to Deep Learning in Python
Petunjuk latihan
- Fit the
model. Remember that the first argument is the predictive features (predictors), and the data to be predicted (target) is the second argument.
Latihan interaktif praktis
Cobalah latihan ini dengan menyelesaikan kode contoh berikut.
# Import necessary modules
from tensorflow.keras.layers import Dense
from tensorflow.keras.models import Sequential
# Specify the model
n_cols = predictors.shape[1]
model = Sequential()
model.add(Dense(50, activation='relu', input_shape = (n_cols,)))
model.add(Dense(32, activation='relu'))
model.add(Dense(1))
# Compile the model
model.compile(optimizer='adam', loss='mean_squared_error')
# Fit the model
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