mljar-supervised
An Automated Machine Learning Python package for tabular data with feature engineering, hyperparameter tuning, explanations, and automatic documentation.
What is mljar-supervised?
MLJAR AutoML is a Python package that automates the machine learning workflow for tabular data. It handles everything from data preprocessing and feature engineering to model training, hyperparameter tuning, and generating detailed documentation. It solves the problem of time-consuming manual ML pipeline construction by providing a streamlined, automated approach with built-in explainability.
Data scientists, ML engineers, and analysts working with structured data who want to accelerate model development, ensure reproducibility, and gain insights into model behavior without sacrificing transparency.
Developers choose MLJAR AutoML for its balance of automation and transparency, offering multiple tailored modes, extensive model explanations, and automatic report generation, all while supporting a wide range of algorithms and fairness-aware training.
Overview
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Use Cases
Best For
- Quickly prototyping machine learning models on tabular datasets
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