Delete app.py.py

app.py.py

@@ -1,42 +0,0 @@
-# -*- coding: utf-8 -*-
-"""Gradio-regression.ipynb
-
-Automatically generated by Colaboratory.
-
-Original file is located at
-    https://colab.research.google.com/drive/1qmfhcPafAIfczazACroyAYyRohdQbklK
-"""
-import numpy as np
-import matplotlib.pyplot as plt
-import seaborn as sns
-import gradio as gr
-from sklearn.linear_model import Ridge, LinearRegression
-from sklearn.model_selection import train_test_split
-np.random.seed(2)
-
-X = 2 * np.random.rand(100, 1)
-y = 4 + 3 * X
-
-X_train, X_test, y_train, y_test = train_test_split(
-    X, y, test_size=0.1, random_state=42)
-
-def build_model(alpha):
-  r_reg = Ridge(alpha=alpha)
-  r_reg.fit(X_train, y_train)
-  return r_reg
-
-def predict(alpha):
-  ridge_reg = build_model(alpha)
-  preds = ridge_reg.predict(X_test)
-  fig = plt.figure()
-  plt.plot(X_test, y_test, "r-")
-  plt.plot(X_test, preds, "b--")
-  plt.title("Effect of regularization parameter on Ridge regression")
-  plt.ylabel("Y")
-  plt.xlabel("X")
-  return plt
-
-inputs = gr.Number()
-outputs = gr.Plot()
-gr.Interface(fn = predict, inputs = inputs, outputs = outputs).launch()
-