모델 사용

Python으로 시작하는 Deep Learning

Dan Becker

Data Scientist and contributor to Keras and TensorFlow libraries

모델 사용

  • 저장
  • 재로드
  • 예측 수행
Python으로 시작하는 Deep Learning

모델 저장, 재로드, 사용하기

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]
Python으로 시작하는 Deep Learning

모델 구조 확인

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
Python으로 시작하는 Deep Learning

연습해 봅시다!

Python으로 시작하는 Deep Learning

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