From 3886cded86cc8daefdb339bb3ec4bb0831dd466c Mon Sep 17 00:00:00 2001 From: Umachandar Jayachandran Date: Wed, 17 Oct 2018 22:13:38 -0700 Subject: [PATCH] Update read me --- .../machine-learning/README.md | 10 +++----- .../machine-learning/sql/README.md | 23 +++++++++++++++++++ 2 files changed, 26 insertions(+), 7 deletions(-) create mode 100644 samples/features/sql-big-data-cluster/machine-learning/sql/README.md diff --git a/samples/features/sql-big-data-cluster/machine-learning/README.md b/samples/features/sql-big-data-cluster/machine-learning/README.md index 065643c1..a68ba74e 100644 --- a/samples/features/sql-big-data-cluster/machine-learning/README.md +++ b/samples/features/sql-big-data-cluster/machine-learning/README.md @@ -1,14 +1,10 @@ # Machine learning in SQL Server 2019 big data cluster -## SQL Server Machine Learning Services on SQL Master instance +## SQL Server Machine Learning Services -In this example, we are building a machine learning model using R 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. +[sql](sql) -### Instructions - -1. Connect to SQL Server Master instance. - -1. Execute the SQL [sql/book-click-prediction-r.sql](sql/book-click-prediction-r.sql/). +SQL Server machine learning services samples showing R, Python & Java support. ## Machine learning using Spark diff --git a/samples/features/sql-big-data-cluster/machine-learning/sql/README.md b/samples/features/sql-big-data-cluster/machine-learning/sql/README.md new file mode 100644 index 00000000..ebd7959c --- /dev/null +++ b/samples/features/sql-big-data-cluster/machine-learning/sql/README.md @@ -0,0 +1,23 @@ +# SQL Server Machine Learning Services on SQL Master instance + +[book-click-prediction-r.sql](book-click-prediction-r.sql/) + +In this example, we are building a machine learning model using R 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-py.sql](book-click-prediction-py.sql/) + +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-r.sql](book-click-prediction-partitioned-r.sql/) + +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 R script per partition. So we will modify the training script to train model per group of users based on credit rating. The R script will produce N models for the same input data set. + +[book-click-prediction-partitioned-py.sql](book-click-prediction-partitioned-py.sql/) + +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. + +### Instructions + +1. Connect to SQL Server Master instance. + +1. Execute the SQL script.