Skip to main content

State-of-the art Automated Machine Learning python library for Tabular Data

Project description

AutoML Alex

Downloads PyPI - Python Version PyPI CodeFactor Telegram License

State-of-the art Automated Machine Learning python library for Tabular Data

Works with Tasks:

  • Binary Classification

  • Regression

  • Multiclass Classification (in progress...)

Benchmark Results


The bigger, the better
From AutoML-Benchmark




  • Automated Data Clean (Auto Clean)
  • Automated Feature Engineering (Auto FE)
  • Smart Hyperparameter Optimization (HPO)
  • Feature Generation
  • Feature Selection
  • Models Selection
  • Cross Validation
  • Optimization Timelimit and EarlyStoping
  • Save and Load (Predict new data)


pip install automl-alex



🚀 Examples


from automl_alex import AutoMLClassifier

model = AutoMLClassifier(), y_train, timeout=600)
predicts = model.predict(X_test)


from automl_alex import AutoMLRegressor

model = AutoMLRegressor(), y_train, timeout=600)
predicts = model.predict(X_test)


from automl_alex import DataPrepare

de = DataPrepare()
X_train = de.fit_transform(X_train)
X_test = de.transform(X_test)

Simple Models Wrapper:

from automl_alex import LightGBMClassifier

model = LightGBMClassifier(), y_train)
predicts = model.predict_proba(X_test)

model.opt(X_train, y_train,
    timeout=600, # optimization time in seconds,
predicts = model.predict_proba(X_test)

More examples in the folder ./examples:

What's inside

It integrates many popular frameworks:

  • scikit-learn
  • XGBoost
  • LightGBM
  • CatBoost
  • Optuna
  • ...

Works with Features

  • Categorical Features

  • Numerical Features

  • Binary Features

  • Text

  • Datetime

  • Timeseries

  • Image


  • With a large dataset, a lot of memory is required! Library creates many new features. If you have a large dataset with a large number of features (more than 100), you may need a lot of memory.

Realtime Dashboard

Works with optuna-dashboard



$ optuna-dashboard sqlite:///db.sqlite3

Road Map

  • Feature Generation

  • Save/Load and Predict on New Samples

  • Advanced Logging

  • Add opt Pruners

  • Docs Site

  • DL Encoders

  • Add More libs (NNs)

  • Multiclass Classification

  • Build pipelines


Telegram Group

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

automl_alex-1.6.10.tar.gz (34.2 kB view hashes)

Uploaded source

Built Distribution

automl_alex-1.6.10-py3-none-any.whl (52.4 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page