MLJAR AutoML
7.1#3 in automl softwareFrom $20 a monthFree planWebLinuxmacOSSelf-hosted
VisitMLJAR AutoML vs TPOT
What both publish
| Fact | MLJAR AutoML | TPOT |
|---|---|---|
| Integrations | The Python package integrates with Mercury to generate prediction apps that support single predictions and batch CSV predictions. | The installation documentation lists scikit-learn and offers extra scikit-learn extensions through the tpot[sklearnex] installation option. |
| Purpose | MLJAR AutoML automates supervised machine learning for tabular data, including binary classification, multiclass classification, and regression. | TPOT is a Python automated machine learning tool that optimizes machine learning pipelines using genetic programming. |
| Support | MLJAR’s About page invites users to contact the team with questions and says they are happy to help. | The project directs users to its GitHub issues to report bugs or suggest enhancements and to discuss extensions. |
MLJAR AutoML plans
- FreeFree
- mljar-supervised Python packageFree
- Pro$20 a month
- Business$60 a month
- Perpetual license$199, paid once
TPOT plans
- TPOTFree
Pick MLJAR AutoML if…
MLJAR AutoML suits people building supervised models from tabular data who want notebook or Python workflows. It is not aimed at forecasting or time-series modeling, and users should account for variation in reports and explanations.
Pick TPOT if…
TPOT suits Python users building or evaluating machine learning pipelines who want genetic programming and configurable pipeline types. Users should be prepared to supply data that works with their chosen operators.