#34 · Primary category: Classical Machine Learning Frameworks
Alink
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
Project last updated:06/07/24
GitHub Stars
3.6K
Forks
782
Contributors
17
License
Apache-2.0
Why we included this project
Alink is a machine learning platform built on Apache Flink by Alibaba's PAI team, and its main draw is that a wide range of classic algorithms lives in one place. Classification, clustering, regression, association rules, recommendation, graph mining, and feature engineering are all offered as pipeline components, so the same operators serve batch training and live streaming data without switching tools. Java is the native interface, while PyAlink exposes the same components to Python and Jupyter, which matters for teams that work mostly in notebooks. Because pipelines mirror Flink's own operator model, you can chain data sources, transformers, and models into a single execution plan that scales across a cluster instead of a single machine. If you already run Flink for stream processing, Alink is a straightforward way to add modeling without standing up a separate compute stack.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
scikit-learn
scikit-learn: machine learning in Python
pyod
A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
umap
Uniform Manifold Approximation and Projection
imbalanced-learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning