Update save_model.py (#9)

## Summary by Sourcery

New Features:
- Persist a trained Random Forest model using pickle.

models/save_model.py

@@ -1,5 +1,23 @@
+import os
 import pickle
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.datasets import make_classification
+from sklearn.model_selection import train_test_split
 
-# Assuming 'model' is your trained model
-with open('models/your_model.pkl', 'wb') as f:
+# Create the models directory if it doesn't exist
+os.makedirs("models", exist_ok=True)
+
+# Generate synthetic data
+X, y = make_classification(n_samples=1000, n_features=20, random_state=42)
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)
+
+# Train a Random Forest model
+model = RandomForestClassifier(n_estimators=100, random_state=42)
+model.fit(X_train, y_train)
+
+# Save the trained model to the /models directory
+model_path = "models/random_forest_model.pkl"
+with open(model_path, "wb") as f:
     pickle.dump(model, f)
+
+print(f"Random Forest model saved to {model_path}")