9 best Java Machine Learning libraries in 2023
by email@example.com Updated: Jan 2, 2023
Machine learning is an area of computer science that enables the software to learn from examples and experience. Machine learning uses algorithms to parse data, learn from that data, and make determinations about it. As per the IDC report, modern enterprises are using AI to improve their business processes, achieve operational efficiencies and expand revenue opportunities. IBM predicts that more than 80% of developers will integrate AI into one or more applications. When it comes to Machine Learning with Java, there are plenty of libraries out there to help you get started. Some of the popular open source libraries include: JSAT - Java Statistical Analysis Tool, a Java library, Datumbox-framework - an open-source framework written in Java which allows the rapid development Machine Learning and Statistical applications, Mltk - Machine Learning Tool Kit. Full list of the best open source Java Machine Learning libraries below.
Datumbox is an open-source Machine Learning framework written in Java which allows the rapid development of Machine Learning and Statistical applications.
Java 1085 Version:Current License: Permissive (Apache-2.0)
Java Statistical Analysis Tool, a Java library for Machine Learning
Java 693 Version:0.0.9 License: Strong Copyleft (GPL-3.0)
Deep learning library for Java, with fully connected, convolutional, and recurrent layers. Also features many gradient descent optimization algorithms.
Java 125 Version:Current License: No License
Machine Learning Java Projects
Java 40 Version:Current License: Permissive (Apache-2.0)
A Java library of machine learning algorithms.
HTML 38 Version:Current License: Others (Non-SPDX)
Java 31 Version:Current License: Permissive (MIT)
some classical ML Algorithm implementation with JAVA
Java 19 Version:Current License: No License