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archive the model

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eugene 2023-06-06 19:52:20 +02:00
parent eadd1af64c
commit 327962b0da
1 changed files with 8 additions and 0 deletions
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script5_2.py
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@ -3,6 +3,7 @@ from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder from sklearn.preprocessing import LabelEncoder
from keras.models import Sequential from keras.models import Sequential
from keras.layers import Dense from keras.layers import Dense
import pickle
# Load the dataset # Load the dataset
df = pd.read_csv('data.csv') df = pd.read_csv('data.csv')
@ -33,6 +34,13 @@ model.compile(loss='mean_squared_error', optimizer='adam')
# Train the model # Train the model
model.fit(X_train, y_train, batch_size=64, epochs=10, validation_data=(X_test, y_test)) model.fit(X_train, y_train, batch_size=64, epochs=10, validation_data=(X_test, y_test))
# Save the model to a file
model.save('model.h5')
# Save the encoder to a file
with open('encoder.pkl', 'wb') as f:
pickle.dump(encoder, f)
# Make predictions on new data # Make predictions on new data
new_writer = 'Jim Cash' new_writer = 'Jim Cash'
new_writer_encoded = encoder.transform([new_writer]) new_writer_encoded = encoder.transform([new_writer])