llnl/dmx-learn
A Python package for creating and training deep graphical models for heterogenous data.
This helps data scientists and machine learning engineers analyze large, complex datasets that combine different types of information, such as text, numbers, and categories. It takes in raw, varied data and produces a statistical model that estimates the underlying patterns and distributions within that data. This is for professionals who need to understand and model heterogeneous data at scale.
Use this if you are working with very large, diverse datasets where traditional statistical methods struggle and you need to build complex, explainable models.
Not ideal if your data is small, homogenous, or if you prefer off-the-shelf black-box machine learning models for predictions.
Stars
7
Forks
1
Language
Jupyter Notebook
License
BSD-3-Clause
Category
Last pushed
Mar 13, 2026
Commits (30d)
0
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