In Python machine learning, how do I build a CLI?

In Python machine learning, building a Command Line Interface (CLI) can make your application more user-friendly. This guide will provide an overview of how to create a simple CLI for your machine learning model using popular libraries.

Python, Machine Learning, CLI, Command Line Interface, Argparse, Click

This example uses the Argparse library in Python to build a simple CLI that allows users to input data for prediction using a machine learning model.

import argparse
import joblib

def main():
    parser = argparse.ArgumentParser(description="Simple CLI for ML Prediction")
    parser.add_argument('--input', type=float, nargs='+', help='Input features for the model')
    args = parser.parse_args()

    model = joblib.load('my_model.pkl')
    prediction = model.predict([args.input])
    print(f"Prediction: {prediction[0]}")

if __name__ == "__main__":
    main()

Python Machine Learning CLI Command Line Interface Argparse Click

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