Build Status PyPI version PyPI pyversions

Automated Machine Learning

mljar-supervised is an Automated Machine Learning python package. It can train ML models for:

What's good in it?

AutoML leaderboard

The example for Decision Tree summary: Decision Tree summary

The example for LightGBM summary: Decision Tree summary

Quick example

There is a simple interface available with fit and predict methods.

import pandas as pd
from supervised.automl import AutoML

df = pd.read_csv("", skipinitialspace=True)

X = df[df.columns[:-1]]
y = df["income"]

automl = AutoML(results_path="directory_with_reports"), y)

predictions = automl.predict(X)

For details please check AutoML API Docs.



From PyPi repository:

pip install mljar-supervised

From source code:

git clone
cd mljar-supervised
python install

Installation for development

git clone
virtualenv venv --python=python3.6
source venv/bin/activate
pip install -r requirements.txt
pip install -r requirements_dev.txt


The mljar-supervised is an open-source project created by MLJAR. We care about ease of use in the Machine Learning. The provides a beautiful and simple user interface for building machine learning models.