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

• binary classification,
• multi-class classification,
• regression.

There is simple interface available with fit and predict methods.

import pandas as pd
from supervised.automl import AutoML

df = pd.read_csv("https://raw.githubusercontent.com/pplonski/datasets-for-start/master/adult/data.csv", skipinitialspace=True)

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

automl = AutoML()
automl.fit(X, y)

predictions = automl.predict(X)

For details please check AutoML API Docs.

From source code:

git clone https://github.com/mljar/mljar-supervised.git
cd mljar-supervised
python setup.py install

From PyPi repository (PyPi can be not updated, it is better to install from source):

pip install mljar-supervised

Installation for development

git clone https://github.com/mljar/mljar-supervised.git
virtualenv venv --python=python3.6
source venv/bin/activate
pip install -r requirements.txt
pip install -r requirements_dev.txt