add the API
Browse files- app.py +38 -0
- notebook.ipynb +0 -0
- scaling.pkl +0 -0
- templates/home.html +11 -0
app.py
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import pickle
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from flask import Flask , request, jsonify, redirect, render_template
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import pandas as pd , numpy as np
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app=Flask(__name__)
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## load the model
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model = pickle.load(open('regression_model.pkl', 'rb'))
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scaling = pickle.load(open('scaling.pkl', 'rb'))
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@app.route('/')
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def home():
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return render_template('home.html')
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@app.route('/predict_api', methods = ['POST'])
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def predict_api():
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data = request.json['data']
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data = np.array(list(data.values())).reshape(1,-1)
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# data = list(np.array(data.values()))
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new_data = scaling.transform(data)
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output = model.predict(new_data)
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return jsonify(output[0])
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# @app.route('/predict')
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# def predict():
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if __name__ == '__main__':
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app.run(debug=True)
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notebook.ipynb
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The diff for this file is too large to render.
See raw diff
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scaling.pkl
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Binary file (938 Bytes). View file
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templates/home.html
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Document</title>
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</head>
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<body>
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<h1>Hello bhai </h1>
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</body>
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</html>
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