Bug fixes. Refactored of scripts & README content.

samples/features/sql-big-data-cluster/machine-learning/sql/python/README.md

@@ -4,13 +4,13 @@ SQL Server 2016 added capability to run R script from T-SQL. SQL Server 2017 add
 
 [book-click-prediction-py.sql](book-click-prediction-py.sql/)
 
-**Applies to: SQL Server 2017+, SQL Server 2019, SQL Server 2019 big data cluster**
+**Applies to:** SQL Server 2017+, SQL Server 2019, SQL Server 2019 big data cluster
 
 In this example, we are building a machine learning model using Python and a logistic regression algorithm for a recommendation engine on an online store. Based on existing users' click pattern online and their interest in other categories and demographics, we are training a machine learning model. This model will then be used to predict if the visitor is interested in a given item category using the T-SQL PREDICT function.
 
 [book-click-prediction-partitioned-py.sql](book-click-prediction-partitioned-py.sql/)
 
-**Applies to: SQL Server 2019, SQL Server 2019 big data cluster**
+**Applies to:** SQL Server 2019, SQL Server 2019 big data cluster
 
 In this example, we are leveraging the new partitioning support (SQL Server 2019) in sp_execute_external_script to partition the input data and run the Python script per partition. So we will modify the training script to train model per group of users based on credit rating. The Python script will produce N models for the same input data set.