Final Project Part 8: Deployment

Save with Joblib

import joblib

joblib.dump(pipeline, 'churn_model.pkl')

Simple Flask API

from flask import Flask, request, jsonify

import joblib

app = Flask(__name__)

model = joblib.load('churn_model.pkl')

@app.route('/predict', methods=['POST'])

def predict():

data = request.json

prediction = model.predict([data['features']])

return jsonify({'churn': int(prediction[0])})

*Day 149: Monitoring and Maintenance.*