Create app.py

app.py

@@ -0,0 +1,103 @@
+import streamlit as st
+import numpy as np
+import pickle
+import streamlit.components.v1 as components
+from sklearn.preprocessing import LabelEncoder
+le = LabelEncoder()
+
+
+
+# Load the pickled model
+def load_model():
+    return pickle.load(open('Number_of_orders_Prediction_LinearRegression.pkl', 'rb')) #change
+
+# Function for model prediction
+def model_prediction(model, features):
+    predicted = str(model.predict(features)[0])
+    return predicted
+
+
+
+def app_design():
+    # Add input fields for High, Open, and Low values
+    image = '24.jpg' #change
+    st.image(image, use_column_width=True)
+    
+    st.subheader("Enter the following values:") #change
+
+    Store_id = st.number_input("Day of week")
+    Store_Type = st.text_input("Week of year")
+    Store_Type = le.transform([Store_Type])
+    Location_Type= st.text_input("Year")
+    Location_Type = le.transform([Location_Type])
+    Region_Code = st.text_input("Period Of Day")
+    Region_Code = le.transform([Region_Code])
+    Date = st.number_input("Forecast Wind Production")
+    Date = le.transform([Date])
+    Holiday  = st.number_input("System Load EA")
+    Discount = st.text_input("SMPEA")
+    Discount = le.transform([Discount])  
+    Order2 = st.number_input("ORK Winds peed")
+    
+    
+    
+    
+    
+    
+        
+    
+    
+    
+        
+    
+ 
+    # Create a feature list from the user inputs
+    features = [[Store_id,Store_Type,Location_Type,Region_Code,Date,Holiday,Discount,Order2]]
+    
+    # Load the model
+    model = load_model()
+    
+    # Make a prediction when the user clicks the "Predict" button
+    if st.button('Predict Orders'):
+        predicted_value = model_prediction(model, features)
+      
+        st.success(f"The orders are: {predicted_value}")       
+
+
+def about_hidevs():
+
+        components.html("""
+        <div>
+        <h4>🚀 Unlock Your Dream Job with HiDevs Community!</h4>
+        <p class="subtitle">🔍 Seeking the perfect job? HiDevs Community is your gateway to career success in the tech industry. Explore free expert courses, job-seeking support, and career transformation tips.</p>
+        <p class="subtitle">💼 We offer an upskill program in <b>Gen AI, Data Science, Machine Learning</b>, and assist startups in adopting <b>Gen AI</b> at minimal development costs.</p>
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+        <p class="subtitle">💡 Join us now, and turbocharge your career!</p>
+        <p class="subtitle"><a class="link" href="https://hidevscommunity.wixsite.com/hidevs" target="__blank">Website</a>
+        <a class="link" href="https://www.youtube.com/@HidevsCommunity1307/" target="__blank">YouTube</a>
+        <a class="link" href="https://www.instagram.com/hidevs_community/" target="__blank">Instagram</a>
+        <a class="link" href="https://medium.com/@hidevscommunity" target="__blank">Medium</a>
+        <a class="link" href="https://www.linkedin.com/company/hidevs-community/" target="__blank">LinkedIn</a>
+        <a class="link" href="https://github.com/hidevscommunity" target="__blank">GitHub</a></p>
+      </div>
+        """,
+                    height=600)
+
+def main():
+
+        # Set the app title and add your website name and logo
+        st.set_page_config(
+        page_title="Number of Orders Prediction",
+        page_icon=":chart_with_upwards_trend:",
+        )
+    
+        st.title("Welcome to our Number of Orders Prediction App!")
+    
+        app_design()    
+        st.header("About HiDevs Community")
+        about_hidevs()
+
+if __name__ == '__main__':
+        main()