Last night, I ventured beyond the regular usage of databases and dived deep into the machine learning capabilities embedded within SQL Server. The evening was an cool journey into the unknown, revealing the potential SQL Server holds not just as a database management system, but also as a powerful tool for developers, data scientists and enthusiasts like me. Uding its R and Python integrations, pre-trained models, and more, I'm amazed at how easily analytics and database management can combine in a single environment. Stay tuned as I share more insights and surprises from my exploration. #MachineLearning #SQLServer #DataScience #ContinuousLearning
These are some of the Features of Machine Learning in SQL Server
- SQL Server Machine Learning Services: This is an embedded R and Python execution in SQL Server. It allows execution of R and Python scripts from T-SQL queries.
- R and Python Integration: With the integration of R and Python in SQL Server, users can run R and Python scripts, and they can also leverage the rich library ecosystem of both languages for data analysis and machine learning.
- Pre-trained Models: SQL Server provides certain pre-trained models that can be directly used for specific tasks such as sentiment analysis or image classification.
- Native Scoring: Using the PREDICT function, trained models can be used for scoring in real-time within SQL Server, without the need for the R or Python runtime.
- Data Exploration & Visualization: With integrated R and Python, data stored in SQL Server can be directly explored and visualized.
- In-Database Analytics: With this feature, the data doesn't need to be moved out of SQL Server for analytics or prediction. This helps in maintaining data security and faster processing as data stays in the database during analysis.
- Stored Procedures: With the sp_execute_external_script stored procedure, you can run any R or Python script directly within SQL Server.
- RevoScaleR and revoscalepy Libraries: These proprietary libraries by Microsoft are optimized for SQL Server and allow for scalable and performant analytics.
- Integration with Azure ML: SQL Server can integrate with Azure Machine Learning, allowing you to store and retrieve ML models and also deploy models from Azure to SQL Server.
#MachineLearning #SQLServer #DataScience #ContinuousLearning
