An in-database machine learning solution to run python models in Postgres

The codebase for DBSim

Demo of an In-database processing tool for scikit-learn

Tools to create database-specific text value embeddings from word embedding datasets

Caret R Models Deployment using SQL databases

Loading, accessing and visualizing data from Netezza Performance server

Data analytics and prediction using Netezza Performance Server

Master's thesis implementation of SQLSIM: executing similarity queries and clustering directly in PostgreSQL to enable in-database analytics.

Linear Regression Benchmark Workflows repository For the VLDB 2018 Research Paper "AIDA - Abstraction for Advanced In-Database Analytics"

Apache MADlib is an open-source library for scalable in-database analytics. It provides data-parallel implementations of mathematical, statistical, and machine learning methods for structured and unstructured data, executed within PostgreSQL or Greenplum Database.