モデルの使用
Pythonで学ぶDeep Learning入門
Dan Becker
Data Scientist and contributor to Keras and TensorFlow libraries
モデルの使用
- 保存
- 再読み込み
- 予測
モデルの保存、再読み込み、使用
from tensorflow.keras.models import load_model
model.save('model_file.h5')
my_model = load_model('model_file.h5')
predictions = my_model.predict(data_to_predict_with)
probability_true = predictions[:,1]
モデル構造の確認
my_model.summary()
_____________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
=========================================================================================
dense_1 (Dense) (None, 100) 1100 dense_input_1[0][0]
_____________________________________________________________________________________________
dense_2 (Dense) (None, 100) 10100 dense_1[0][0]
_____________________________________________________________________________________________
dense_3 (Dense) (None, 100) 10100 dense_2[0][0]
_____________________________________________________________________________________________
dense_4 (Dense) (None, 2) 202 dense_3[0][0]
=========================================================================================
Total params: 21,502
Trainable params: 21,502
Non-trainable params: 0
演習に進みましょう！
Pythonで学ぶDeep Learning入門
