Machine Learning

Libraries for Machine Learning. Also see awesome-machine-learning.

Search every project in one place

Press / to search. Tap a tag to filter. Click any row for details.

Search and filter

Filtering for

Results

Row number Tags
The most popular Python library for Machine Learning with extensive documentation and community support.
scikit-learn/github.com/scikit-learn/scikit-learn /
Apache Spark's scalable Machine Learning library for distributed computing.
apache/github.com/apache/spark /
MindsDB is an open source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning models using standard queries.
mindsdb/github.com/mindsdb/mindsdb /
A scalable, portable, and distributed gradient boosting library.
dmlc/github.com/dmlc/xgboost /
A pretrained foundation model from Google Research for time-series forecasting.
google-research/github.com/google-research/timesfm /
A fast, distributed, high performance gradient boosting framework.
lightgbm-org/github.com/lightgbm-org/LightGBM /
A fast, scalable, high performance gradient boosting on decision trees library.
catboost/github.com/catboost/catboost /
Open Source Fast Scalable Machine Learning Platform.
h2oai/github.com/h2oai/h2o-3 /
A Python library for probabilistic graphical models and Bayesian networks.
pgmpy/github.com/pgmpy/pgmpy /
sklearn compatible API with the widest toolset for feature engineering and selection.
feature-engine/github.com/feature-engine/feature_engine /
Synthetic tabular data generation using GANs, Diffusion Models, and LLMs.
Diyago/github.com/Diyago/Tabular-data-generation /

Contribute

Know a project that belongs here?

Tell us what it does and why it stands out.

Submit a project Star the repository