save machine learning model
# fit the model
model.fit(X_train, y_train)
# save the model
import pickle
pickle.dump(model, open("model.pkl", "wb"))
# load the model
model = pickle.load(open("model.pkl", "rb"))
# use model to predict
y_pred = model.predict(X_input)load model keras
from tensorflow import keras
model = keras.models.load_model('path/to/location')save machine learning model python
model.fit(X_train, Y_train)
# save the model to disk
filename = 'finalized_model.sav'
pickle.dump(model, open(filename, 'wb'))
# load the model from disk
loaded_model = pickle.load(open(filename, 'rb'))
result = loaded_model.score(X_test, Y_test)how to load keras model from json
json_file = open('model.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model = model_from_json(loaded_model_json)
# load weights into new model
loaded_model.load_weights("model.h5")Copyright © 2021 Codeinu
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