Upload 5 files

apk.py

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+import numpy as np
+from flask import Flask, request, jsonify, render_template
+import pickle
+
+app = Flask(__name__)
+model = pickle.load(open('model.pkl', 'rb'))
+
+@app.route('/')
+def home():
+    return render_template('index.html')
+
+@app.route('/predict',methods=['POST'])
+def predict():
+    '''
+    For rendering results on HTML GUI
+    '''
+    int_features = [int(x) for x in request.form.values()]
+    final_features = [np.array(int_features)]
+    prediction = model.predict(final_features)
+
+    output = round(prediction[0], 2)
+
+    return render_template('index.html', prediction_text='Employee Salary should be $ {}'.format(output))
+
+
+if __name__ == "__main__":
+    app.run(debug=True)

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6d4fc0a54a5e4a44a6e91da98abd889eb38337f105368de72cc44795b1fcb3b6
+size 582

request.py

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+import requests
+
+url = 'http://localhost:5000/predict_api'
+r = requests.post(url,json={'experience':2, 'test_score':9, 'interview_score':6})
+
+print(r.json())

requirements.txt

@@ -0,0 +1,125 @@
+anyio @ file:///C:/ci/anyio_1644481856696/work/dist
+appdirs==1.4.4
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+attrs @ file:///C:/b/abs_09s3y775ra/croot/attrs_1668696195628/work
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+backcall @ file:///home/ktietz/src/ci/backcall_1611930011877/work
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+brotlipy==0.7.0
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+jsonschema @ file:///C:/b/abs_6ccs97j_l8/croot/jsonschema_1676558690963/work
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+wincertstore==0.2

templates/index.html

@@ -0,0 +1,35 @@
+<!DOCTYPE html>
+<html >
+<!--From https://codepen.io/frytyler/pen/EGdtg-->
+<head>
+  <meta charset="UTF-8">
+  <title>ML API</title>
+  <link href='https://fonts.googleapis.com/css?family=Pacifico' rel='stylesheet' type='text/css'>
+<link href='https://fonts.googleapis.com/css?family=Arimo' rel='stylesheet' type='text/css'>
+<link href='https://fonts.googleapis.com/css?family=Hind:300' rel='stylesheet' type='text/css'>
+<link href='https://fonts.googleapis.com/css?family=Open+Sans+Condensed:300' rel='stylesheet' type='text/css'>
+  
+</head>
+
+<body>
+ <div class="login">
+	<h1>Predict Salary Analysis</h1>
+
+     <!-- Main Input For Receiving Query to our ML -->
+    <form action="{{ url_for('predict')}}"method="post">
+    	<input type="text" name="experience" placeholder="Experience" required="required" />
+        <input type="text" name="test_score" placeholder="Test Score" required="required" />
+		<input type="text" name="interview_score" placeholder="Interview Score" required="required" />
+
+        <button type="submit" class="btn btn-primary btn-block btn-large">Predict</button>
+    </form>
+
+   <br>
+   <br>
+   {{ prediction_text }}
+
+ </div>
+
+
+</body>
+</html>