Update README.md

Author: RK-Sharath

README.md

@@ -272,7 +272,7 @@ We can observe that attributes like Married, Applicant Income & Credit history a
 
 ![](https://github.com/IBM/predict-fraud-using-auto-ai/blob/master/images/shap_ft_imp.png)
 
-With this, we have come to the end of this code pattern where we can compare the ease of using AutoAI to build predictive models vs creating a new jupyter notebook to build and evaluate predictive models. `There's considerable reduction of time in building and deploying the models using AutoAI because it handles missing values, outliers, feature engineering & hyper parameters optimization on the fly and selects the best algorithm as per the dataset.` If you are a developer or a data scientist who wants to build the model quickly and deploy it for being production ready, then AutoAI is for you which will help in taking decisions faster and gives a detailed overview of the attribute relationships within the data. 
+With this, we have come to the end of this code pattern where we can compare the ease of using AutoAI to build predictive models vs creating a new jupyter notebook to build and evaluate predictive models. `There's considerable reduction of time in building and deploying the models using AutoAI because it handles missing values, outliers, feature engineering & hyper parameters optimization on the fly and selects the best algorithm as per the dataset.` AI Model building process has been reduced from Days to Hours thanks to `AutoAI.` If you are a developer or a data scientist who wants to build the model quickly and deploy it for being production ready, then AutoAI is for you which will help in taking decisions faster and gives a detailed overview of the attribute relationships within the data. 
 
 ## More to come :