shankarpandala / lazypredict
Python AutoML toolkit for benchmarking classification, regression, and time-series forecasting models, with GPU acceleration, MLflow tracking, and automated preprocessing.
Why this job: matched by what the repo talks about: benchmark, model, regression, time
What it does
- Over 40 built-in machine learning models
- Automatic model selection for classification, regression, and time series forecasting
- 20+ forecasting models. statistical (ETS, ARIMA, Theta), ML (Random Forest, XGBoost, etc.), deep learning (LSTM, GRU), and pretrained foundation models (TimesFM)
- Automatic seasonal period detection via ACF
- Multiple categorical encoding strategies (OneHot, Ordinal, Target, Binary)
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 10 days ago
- Stars
- 3,350
- +1 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.4.0
- Released 10 days ago
- Built with
- Python
- 98% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 100% closed
- 1 still open
- Pull requests
- 126 merged
- 0 waiting
- Releases
- 13
- 8 in the last year
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
More: languages, topics and project record
Languages
- Python 98%
- TeX 2%
- Makefile <1%
Topics
- machine-learning
- automl
- regression
- classification
Project record
- JobEvals and observability
- StatusListed
- Commits471
- Forks366
- Watching25
- Stars in 28 days+4
- CreatedNov 16, 2019
- First seen by usNov 7, 2026
- CheckedNov 8, 2026