Update README.md

README.md

@@ -38,7 +38,7 @@ And we will focus solely on restaurants, so we will follow these steps to get ou
 - Load `yelp_academic_dataset_business.json` and `yelp_academic_dataset_review.json` as pandas DataFrames.
 - Perform an inner merge of these datasets based on `business_id` and filter out businesses that are not restaurants (filter out rows that `categories` doesn't contain "restaurants").
 - Split the yelp restaurants dataset into a training dataset and a testing dataset by shuffling the dataset and then spliting it by 80/20.
-- Finally, we get yelp restaurants [training](https://yelpdata.s3.us-west-2.amazonaws.com/yelp_train.csv) and [testing](https://yelpdata.s3.us-west-2.amazonaws.com/yelp_test.csv) datasets
+- Finally, we get yelp restaurants [training](https://yelpdata.s3.us-west-2.amazonaws.com/yelp_train.csv) and [testing](https://yelpdata.s3.us-west-2.amazonaws.com/yelp_test.csv) datasets in CSV format.
 (You may check the data processing by this link: [Data Process Colab Link](https://colab.research.google.com/drive/1r_gUGmsawwtFpZCj23X1jWjfEi6Dw291?usp=sharing))
 
 ## Restaurant Dataset