sql-machine-learning/sqlflow
Sqlflow
sqlflow is a SQL machine learning engine and orchestrator designed for training, deploying, and explaining machine learning models using extended SQL query syntax. It enables in-database machine learning by connecting database engines to external machine learning toolkits, allowing users to define training datasets and hyperparameters directly through queries.
The system functions as a prediction interface and explainability tool. It allows for generating classifications and predictions on database records by calling model functions within standard SQL statements and provides a workflow to interpret how specific features influence model decisions.
Features
- SQL-Based Machine Learning - Defines machine learning training and inference parameters using a custom SQL query syntax.
- In-Database Machine Learning - Enables the training and execution of machine learning models directly within the database engine using SQL.
- Machine Learning Toolkits - Integrates with specialized machine learning toolkits to facilitate model training and prediction execution.
- Machine Learning Training - Supports building machine learning models by defining datasets and hyperparameters via SQL syntax.
- Model Inference - Enables model inference by calling prediction functions directly within SQL select statements.
- Model Predictions - Generates predicted values and classifications from trained models using standard SQL queries.
- Model Explainability - Uses query extensions to quantify the influence of specific features on model predictions.
- AI and Machine Learning - SQL-based machine learning engine.
- Machine Learning Operations - Brings machine learning capabilities to SQL, enabling model training and prediction using SQL syntax.
- Data Processing Tools - Bridge between SQL queries and machine learning workflows.
