diff --git a/Student assignment updates.txt b/Student assignment updates.txt
index 9979d7c..c8acc77 100644
--- a/Student assignment updates.txt	
+++ b/Student assignment updates.txt	
@@ -1,2 +1,3 @@
-Write your name and PRN no
+Name:Gayatri Sopan Gade
+PRN:2020BTECS00210
 Hello Updated
diff --git a/assignment2.py b/assignment2.py
new file mode 100644
index 0000000..1c7015a
--- /dev/null
+++ b/assignment2.py
@@ -0,0 +1,63 @@
+# -*- coding: utf-8 -*-
+"""Assignment2.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1uLqr_xv_w9FyRqQyk7gDjuOH39EVvHXG
+"""
+
+from google.colab import drive
+drive.mount('/content/drive')
+
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+
+from sklearn.linear_model import LinearRegression
+from sklearn.model_selection import train_test_split
+
+print('Booting into Machine Learning....')
+
+data=pd.read_csv('/content/drive/MyDrive/hour.csv')
+
+data.head(10)
+
+print('Defining variables')
+X = data['atemp']
+y = data['registered']
+
+plt.scatter(X,y, color='green')
+
+print('Splitting the data into hour')
+X_hour, X_test, y_hour, y_test = train_test_split(X,y,random_state=0)
+
+plt.scatter(X_hour,y_hour, color='green')
+
+plt.scatter(X_test,y_test, color='green')
+
+print('Training the model using X_hour, y_hour')
+lr = LinearRegression()
+
+#print(X_hour)
+#print(y_hour)
+#print(X_hour.values.reshape(-1,1))
+lr.fit(X_hour.values.reshape(-1,1),y_hour)
+
+print('Predicting using the trained model - X_hour')
+y_pred=lr.predict(X_test.values.reshape(-1,1))
+
+print(y_test) #Test data - actual data
+print(y_pred) #Model predicted dataset
+
+plt.scatter(X_hour,y_hour,color='green')
+plt.scatter(X_test,y_pred,color='red')
+
+plt.xticks()
+plt.yticks()
+plt.show()
+
+print('Finding intercept & coeff')
+print('Intercept', lr.intercept_)
+print('Coefficient', lr.coef_)
+print(lr.coef_,'x +',lr.intercept_)
\ No newline at end of file