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@@ -573,9 +573,11 @@ _Tools that provide specific statistical algorithms for learning from data._
 - [DJL](https://djl.ai) - High-level and engine-agnostic framework for deep learning.
 - [H2O ![c]](https://www.h2o.ai) - Analytics engine for statistics over big data.
 - [JSAT](https://github.com/EdwardRaff/JSAT) - Algorithms for pre-processing, classification, regression, and clustering with support for multi-threaded execution. (GPL-3.0-only)
+- [oj! Algorithms](https://www.ojalgo.org/) - High-performance mathematics, linear algebra and optimisation needed for data science, machine learning and scientific computing.
 - [Oryx 2](https://github.com/OryxProject/oryx) - Framework for building real-time, large-scale machine learning applications. Includes end-to-end applications for collaborative filtering, classification, regression, and clustering.
 - [Siddhi](https://github.com/siddhi-io/siddhi) - Cloud native streaming and complex event processing engine.
 - [Smile](https://github.com/haifengl/smile) - Statistical Machine Intelligence and Learning Engine provides a set of machine learning algorithms and a visualization library.
+- [Tribuo](https://tribuo.org/) - Provides tools for classification, regression, clustering, model development and interfaces with other libraries such as scikit-learn, pytorch and TensorFlow.
 - [Weka](https://www.cs.waikato.ac.nz/ml/weka/) - Collection of algorithms for data mining tasks ranging from pre-processing to visualization. (GPL-3.0-only)
 
 ### Messaging