Update basics.ipynb

Author: Sarvesh-Kesharwani

site/en/guide/basics.ipynb

@@ -784,7 +784,7 @@
         "id": "7EWyDu3zot2w"
       },
       "source": [
-        "Write a basic training loop for the model. The loop will make use of the MSE loss function and its gradients with respect to the input in order to iteratively update the model's parameters. Using mini-batches for training provides both memory efficienciy and faster convergence. The `tf.data.Dataset` API has useful functions for batching and shuffling."
+        "Write a basic training loop for the model. The loop will make use of the MSE loss function and its gradients with respect to the input in order to iteratively update the model's parameters. Using mini-batches for training provides both memory efficiency and faster convergence. The `tf.data.Dataset` API has useful functions for batching and shuffling."
       ]
     },
     {