Code Snippets for saving and loading different machine learning models

save_and_load.py

#Keras Models

#---Save---#
json_file = model.to_json()
with open(json_file_path, "w") as file:
   file.write(json_file)
model.save_weights(h5_file)

#---Load---#
from keras.models import model_from_json
file = open(json_file, 'r')
model_json = file.read()
file.close()
loaded_model = model_from_json(model_json)
loaded_model.load_weights(h5_file)


#Scikit-Learn Models

#---Save---#
from sklearn.linear_model import LogisticRegression
import pickle
model = LogisticRegression()
model.fit(xtrain, ytrain)
pickle.dump(model, open(model_file_path, 'wb'))

#---Load---#
model = pickle.load(open(model_file_path, 'rb'))
result_val = model.score(xval, yval)
result_test = model.score(xtest, ytest)

#StatsModel Models

#---Save---#
import statsmodels.api as sm
model = sm.tsa.ARIMA([1,5,9,12], order=(1, 0, 1))  
my_model= model.fit()
my_model.save(myfile)

#---Load---#
from statsmodels.tsa.arima_model import ARIMAResults
loaded = ARIMAResults.load(my_file)