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data-science GitHub repositories

Explore 129 tracked GitHub repositories tagged data-science. Compare their recorded star activity and implementation languages, then follow related topics to find other projects.

Snapshot: 2026-10-28. The collection gained 340 stars since the previous daily snapshot.

Tracked repositories
129
Total stars
1,086,306
Stars gained · 7 days
+1,967
Stars gained · 30 days
+8,232

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Star activity for data-science repositories on this page
RepositoryTotal starsToday7 days30 days
apache/hamilton2.6K+1+5+19
aws/amazon-sagemaker-examples11.0K+1+5+11
h2oai/h2o-37.5K+1+4+6
skforecast/skforecast1.5K+1+4+5
neonwatty/machine-learning-refined2.3K+1+3+53

Explore repositories

Showing 51–100 of 129 tracked repositories.

h2oai/h2o-3

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

perpetual-ml/perpetual

Perpetual is a high-performance gradient boosting machine. It delivers optimal accuracy in a single run without complex tuning through a simple budget parameter. It features out-of-the-box support for causal ML, continual learning, native calibration, and robust drift monitoring, along with Rust core and zero-copy bindings for Python and R

WenjieDu/PyPOTS

A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific analysis tasks (imputation, classification, clustering, forecasting, anomaly detection, cleaning) on incomplete industrial irregularly-sampled multivariate TS with NaN missing values

lzz19980125/awesome-time-series-segmentation-papers

This repository contains a reading list of papers on Time Series Segmentation. This repository is still being continuously improved.

microsoft/responsible-ai-toolbox

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.