Best Libraries for Implementing Machine Learning in Java

Skills in machine learning or deep learning are some of the most important topics under discussion in the world of technology these days. Moreover, several companies around the world are currently hunting for programmers who have excellent knowledge of ML. Java is one of the most popular languages right now, right after Python. Java is also a norm for programmers when working with ML algorithms nowadays.


One of the many advantages that you can get when learning Java is that you can also work with the ML community and expand your skills o marketability, easy maintenance, and readability. This article will give you a list of 10 best machine learning libraries that you can use when working with Java. The following Java machine learning libraries have been selected based on their popularity and ease of use.


Adams is short for Advanced Data mining And Machine learning System. The Java machine learning library of Adams is a strong follower of “Less is more.” It follows a minimalistic approach. Adams is a novel as well as a flexible workflow engine and allows you to build as well as maintain real-world workflows, which can be quite complex.


Deeplearning4j is also one of the libraries specifically designed for Java. It has a huge level of support for deep learning algorithms. The community of Java also calls it one of the most innovative contributors to the ecosystem of Java. Furthermore, Deeplearning4j is an open-source that is linked together to connect deep neural networks as well as deep reinforcement learning. Designers often call it the DIY tool for Java.


Elki is an acronym for Environment for Developing KDD-Applications through index-structure. ELKI is also an open-source library software with Java. It contains a variety of configurable algorithms and parameters for Java. Graduate students use it occasionally to construct data sets. The primary use of ELKI is research and teaching, and that is what its software network is based on. The library hopes to develop as well as evaluate advanced data mining algorithms as well as all of their interactions.


JavaML is a collection of machine learning and data mining algorithms designed with Java. The main purpose of this library is that both software developers, as well as research scientists, can use it. Its interfaces are quite simple and easy to use. Even though the library does not have its own GUI, it still has interfaces for every algorithm.


JSAT stands for Java Statistical Analysis Tool. It is clear by its name that JSAT is a java library of machine learning, whose purpose of getting ML problems quickly started. One part of the library is strictly dedicated to self-education. The codes of the library are self-contained, which means that they do not have any external dependencies.


These are some of the best-rated libraries to use with Java. Now that you have the right information, you can choose your library accordingly.

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