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app.py

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+import gradio as gr
+import pandas as pd
+import numpy as np
+from sklearn.linear_model import LinearRegression
+import pickle
+filename = 'finalized_model.sav'
+
+
+# load the model from disk
+lineareg = pickle.load(open(filename, 'rb'))
+
+
+#function to predict the input hours
+def predict_score(hours):
+    hours = np.array(hours)
+    pred_score = lineareg.predict(hours.reshape(-1,1))
+    return np.round(pred_score[0], 2)
+
+input = gr.inputs.Number(label='Number of Hours studied')
+output = gr.outputs.Textbox(label='Predicted Score')
+gr.Interface( fn=predict_score,
+              inputs=input,
+              outputs=output).launch();
+