MLJAR AutoML

We’re on our way to revolutionizing the field of machine learning and data analysis. Whether you're a small startup or a large enterprise, MLJAR is here to support you on your machine learning journey.

Features

Discover the unique features that make our AutoML the state of the art. Find those that make your ML project advanced, super easy, and understandable.

Complete pipeline

Simplifies the entire machine learning process from data preprocessing to model deployment.

Golden feature

Efficiently pinpoints the most influential variables for optimal model performance.

Model leaderboard

Enables easy comparison and selection of models based on performance metrics.

Automated reports

The report from running AutoML will contain the table with information about each model score and the time needed to train the model.

Feature selection

MLJAR AutoML takes care of features preprocessing like missing values imputation and converting categoricals, it can also handle target values preprocessing.

Auto-saving models

All models in the AutoML are saved and loaded automatically. No need to call save() or load().

Hyperparameter tuning

Optimizes model performance by automatically searching for the best combination of hyperparameters, saving time and effort.

Variety of algorithms

Choose from many algorithms such as: XGBoost, CatBoost, Neural Networks, Decision trees, Random forest and many more...