Update C2_W4_Assignment.ipynb

Corrected an error in the function back propagation for the updation of b1 and b2. Grader now gives an output of 5/5

Author: farhan-najeeb

2 - Natural Language Processing with Probabilistic Models/Labs/Week 4/C2_W4_Assignment.ipynb

@@ -698,9 +698,9 @@
     "    # Compute the gradient of W2\n",
     "    grad_W2 = (1/batch_size)*np.dot(yhat-y,h.T)\n",
     "    # Compute the gradient of b1\n",
-    "    grad_b1 = np.sum((1/batch_size)*np.dot(l1,x.T),axis=1,keepdims=True)\n",
+    "    grad_b1 = np.sum((1/batch_size)*l1,axis=1,keepdims=True)\n    #1/m * relu(w2.T(yhat-y)) . 1mT\n"",
     "    # Compute the gradient of b2\n",
-    "    grad_b2 = np.sum((1/batch_size)*np.dot(yhat-y,h.T),axis=1,keepdims=True)\n",
+    "    grad_b2 = np.sum((1/batch_size)*(yhat-y),axis=1,keepdims=True)\n",
     "    ### END CODE HERE ###\n",
     "    \n",
     "    return grad_W1, grad_W2, grad_b1, grad_b2"