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import pandas as pd
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import os
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from tensorflow.keras.models import load_model
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from joblib import load
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def predict_gender(name, model, tfidf):
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vectorized_name = tfidf.transform([name]).toarray()
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gender = model.predict(vectorized_name) > 0.5
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return 'Male' if gender[0][0] == 1 else 'Female'
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model = load_model('gender_prediction_model.h5')
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tfidf_vectorizer_file = 'tfidf_vectorizer.joblib'
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if not os.path.exists(tfidf_vectorizer_file):
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raise FileNotFoundError(f"{tfidf_vectorizer_file} not found. Please ensure the file exists in the current directory.")
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tfidf = load(tfidf_vectorizer_file)
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while True:
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name = input("Enter a name to predict gender (or type 'exit' to quit): ")
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if name.lower() == 'exit':
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break
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predicted_gender = predict_gender(name, model, tfidf)
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print(f"The predicted gender for '{name}' is: {predicted_gender}")
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