Database Wizard: The backbone of Machine Learning and AI in an agile environment

SQL, AWS, and SQL Server are useful tools that allow one to load, clean, validate, and retrieve relational datasets needed for AI and Machine Learning. AI and Machine Learning rely on data stored in a database. In traditional models where modeling occurs outside of the database, machine learning still depends on SQL data pipelines for data sourcing and data cleansing. Database Driven Machine Learning allows applications to be built inside of the SQL database without moving all of the data as in traditional models facilitating fast production and reducing company overhead. SQL queries implement Machine Language Models directly. AI tables allow database designers to train data. AI tables enable a database to predict missing data based on previous data trends. 


https://www.projectpro.io/article/how-to-become-an-ai-engineer/445

https://www.ijcsmc.com/docs/papers/March2016/V5I3201617.pdf

https://sqream.com/blog/the-role-of-sql-in-machine-learning/

https://www.infoworld.com/article/3607762/8-databases-supporting-in-database-machine-learning.html

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