diff --git a/README.md b/README.md
index 225a66d..945b2a8 100644
--- a/README.md
+++ b/README.md
@@ -12,6 +12,10 @@ Datum provides APIs to create tfrecord daatsets and read tfrecord as `tf.data.Da
 TFRecord enables efficient handling of small or large datasets. Samples of datasets are stored in serialized binary string format.
 The purpose of this library to make it easier for end-user to create and read tfrecord datasets effortlessly.
 
+### Example notebooks on Google Colab
+
+1. Image Classification: [Transfer learning using Datum and Keras](https://colab.research.google.com/drive/1_r34J0MgdC7yCIVtH_EV0ne5q2y6EaH9?usp=sharing).
+2. Text Classification: [BERT based text classofocation using Datum and Tensorflow Text](https://colab.research.google.com/drive/1D5U6NvioF-T8Nhvzzkuskw85Ki1yGR6K?usp=sharing).
 
 ## Getting Started
 
@@ -41,12 +45,6 @@ lazydocs datum --output-path docs/api-docs  --overview-file README.md
 mkdocs serve
 ```
 
-### Example notebooks on Google Colab
-
-1. Image Classification: [Transfer learning using Datum and Keras](https://colab.research.google.com/drive/1_r34J0MgdC7yCIVtH_EV0ne5q2y6EaH9?usp=sharing).
-2. Text Classification: [BERT based text classofocation using Datum and Tensorflow Text](https://colab.research.google.com/drive/1D5U6NvioF-T8Nhvzzkuskw85Ki1yGR6K?usp=sharing).
-
-
 ### Create tfeecord dataset 
 Dataset can be created by using the following command
 ```Shell