SQL Database Optimization

We can use deep reinforcement learning to optimize a SQL database, and in this video we’ll optimize the ordering of a series of SQL queries such that it involves the minimum possible memory/computation footprint. Deep RL involves using a neural network to approximate reinforcement learning functions, like the Q (quality) function. After we frame our database as a Markov Decision Process, I’ll use Python to build a Deep Q Network to optimize SQL queries. Enjoy!

Code for this video:
https://github.com/llSourcell/SQL_Database_Optimization

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More learning resources:

SQL Query Optimization Meets Deep Reinforcement Learning


https://mldb.ai/
https://docs.microsoft.com/en-us/sql/advanced-analytics/what-is-sql-server-machine-learning?view=sql-server-2017
https://towardsdatascience.com/machine-learning-in-your-database-the-case-for-and-against-bigquery-ml-4f2309282fda
https://www.quora.com/Which-database-is-best-for-machine-learning
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