diff --git a/Module 2/Linear Regression.ipynb b/Module 2/Linear Regression.ipynb
index 4652c5d..b64dec6 100644
--- a/Module 2/Linear Regression.ipynb	
+++ b/Module 2/Linear Regression.ipynb	
@@ -149,6 +149,15 @@
     "    cost = 0\n",
     "    # ====================== YOUR CODE HERE ======================\n",
     "    # Instructions: Compute the cost of a particular choice of theta\n",
+    ...
+    h = np.dot(X,theta)
+    for i in range(m):
+        k = (h[i]-y[i])**2
+        cost = cost +k
+    cost = cost / (2*m)
+    ...
+
+
     "    \n",
     "    \n",
     "    \n",
@@ -183,14 +192,22 @@
    "source": [
     "def gradientDescent(X, y, theta, alpha, iterations):\n",
     "    m = len(X) \n",
+    ...
+    y=y.reshape((100,1))
+    ...
     "    for i in range(len(X)):\n",
     "        # ====================== YOUR CODE HERE ======================\n",
     "        # Instructions: Perform a single gradient step on the parameter vector theta. \n",
+    ...
+    theta[0] = theta[0] - alpha * (1/m) * sum(h - y)
+        theta[1] = theta[1] -alpha * (1/m) *sum(np.multiply((h-y),X_init))
+    ...
     "        \n",
     "        \n",
     "        \n",
     "        \n",
     "        # ============================================================\n",
+             # I have made some changes in the range of the loop..i have used iterations instead of m
     "    return theta\n",
     "\n",
     "theta = gradientDescent(X, y, theta, alpha, iterations)\n",