Version2

Author: findtharun

Deploy-As-Service-Using-AWS-EC2/app.py

@@ -0,0 +1,28 @@
+import numpy as np
+import pandas as pd
+from flask import Flask, request, jsonify, render_template
+import pickle
+
+app = Flask(__name__,template_folder='templates')
+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
+    '''
+    features = [x for x in request.form.values()]
+    final_features = [np.array(features)]
+    column_names=['R&DSpend','Administration','MarketingSpend','State']
+    final_features=pd.DataFrame(final_features,columns=column_names)
+    prediction= model.predict(final_features)
+    temp=0.0
+    for i in prediction:
+        for j in i:
+            temp=j
+    return render_template('index.html', prediction_text='${}'.format(temp))
+

Deploy-As-Service-Using-AWS-EC2/model.pkl

@@ -0,0 +1,6 @@
+Flask==1.1.1
+seaborn==0.9.0
+numpy==1.16.2
+pandas==0.25.1
+matplotlib==3.0.3
+scikit_learn==0.23.1

Deploy-As-Service-Using-AWS-EC2/requirements.txt

@@ -0,0 +1 @@
+The scss source files are available in the pro version.