Modified the refernce section

Author: KarthikDutt

guide/14-deep-learning/monitor_model_training_with_tensorboard.ipynb

@@ -13,7 +13,7 @@
    "source": [
     "Training a deep learning model is a long and iterative process and, hence, it is important to have a tool to visualize the progress of the model training and monitor the learning process.\n",
     "\n",
-    "`TensorBoard` is an open source toolkit which enables us to understand training progress and improve model performance by updating the hyperparameters. `TensorBoard` toolkit displays a dashboard where the logs can be visualized as graphs, images, histograms, embeddings, text etc. It also helps in tracking information like gradients, losses, metrics, and intermediate outputs. [[1](#1), [2](#2)]\n",
+    "`TensorBoard` is an open source toolkit which enables us to understand training progress and improve model performance by updating the hyperparameters. `TensorBoard` toolkit displays a dashboard where the logs can be visualized as graphs, images, histograms, embeddings, text etc. It also helps in tracking information like gradients, losses, metrics, and intermediate outputs [[1](#1), [2](#2)].\n",
     "\n",
     "`arcgis.learn` module integrates TensorBoard toolkit to the model training process which now makes it possible for us to monitor model training process. In this guide, we will learn how model training can be monitored using `TensorBoard` within `arcgis.learn` module.\n",
     "\n",