Intial commit

app.py

@@ -0,0 +1,66 @@
+# importing required libraries
+import pickle
+import streamlit as st
+
+# loading the trained model
+pickle_in = open('classifier.pkl', 'rb') 
+classifier = pickle.load(pickle_in)
+
+# this is the main function in which we define our app  
+def main():       
+    # header of the page 
+    html_temp = """ 
+    <div style ="background-color:yellow;padding:13px"> 
+    <h1 style ="color:black;text-align:center;">Check your Loan Eligibility</h1> 
+    </div> 
+    """
+    st.markdown(html_temp, unsafe_allow_html = True) 
+
+    # following lines create boxes in which user can enter data required to make prediction 
+    Gender = st.selectbox('Gender',("Male","Female","Other"))
+    Married = st.selectbox('Marital Status',("Unmarried","Married","Other")) 
+    ApplicantIncome = st.number_input("Monthly Income in Rupees") 
+    LoanAmount = st.number_input("Loan Amount in Rupees")
+    result =""
+      
+    # when 'Check' is clicked, make the prediction and store it 
+    if st.button("Check"): 
+        result = prediction(Gender, Married, ApplicantIncome, LoanAmount) 
+        st.success('Your loan is {}'.format(result))
+ 
+# defining the function which will make the prediction using the data which the user inputs 
+def prediction(Gender, Married, ApplicantIncome, LoanAmount): 
+
+    # 2. Loading and Pre-processing the data 
+
+    if Gender == "Male":
+        Gender = 0
+    else:
+        Gender = 1
+
+    if Married == "Married":
+        Married = 1
+    else:
+        Married = 0
+
+    #3. Building the model to automate Loan Eligibility 
+
+    # if (ApplicantIncome >= 50000):
+    #     loan_status = 'Approved'
+    # elif (LoanAmount < 500000):
+    #     loan_status = 'Approved'
+    # else:
+    #     loan_status = 'Rejected'
+    # return loan_status
+
+    prediction = classifier.predict( 
+        [[Gender, Married, ApplicantIncome, LoanAmount]])
+     
+    if prediction == 0:
+        pred = 'Rejected'
+    else:
+        pred = 'Approved'
+    return pred
+     
+if __name__=='__main__': 
+    main()