“ Machine Learning is aimed at equipping computers with abilities to learn from data and experience and present predictions based on the learning. Approaches to machine learning include decision trees, support vector machines and k-nearest neighbors, and most significantly neural networks which forms the basis of Artificial Intelligence.
Java is widely used in machine learning, software development and creation of Big data ecosystems. Java skills are required in software project maintenance, support, debugging and migration. Choice of the right machine learning tool speeds up the digital transformation process, there is more accuracy in predictions using data while maintaining the current technology stack. ”

Machine Learning Libraries

Machine learning libraries are software tools that provide a set of pre-implemented algorithms, functions, and utilities to facilitate the development, training, and evaluation of machine learning models. These libraries are designed to make it easier for developers and researchers to work with machine learning tasks without having to implement everything from scratch. They typically offer a wide range of algorithms and data processing tools, allowing users to experiment with various approaches and techniques for different machine learning problems.

Neural Networks

Java has simplified the task of training several neural networks. Neural Networks are much like the human brain and the nervous system and purposefully so because the scientists aimed to develop machine intelligence that could imitate human intelligence. Easy Neurons, a Java based GUI tool is used in the development of Neural Networks. Just like the human brain system comprises of interconnected neurons, the artificial neural network is made of interlinked nodes organized into input, intermediate and output layers. These layers are responsible for learning patterns and relationships within the data. Each neuron of intermediate layer takes inputs from the previous layer and applies a process before passing the output to the next layer.
Neural networks have immense compute prowess and learning capacity including complex processing abilities like Natural Language Processing. Deep learning is a type of machine learning system, in which the neural networks have many intermediate layers and hence massive and diverse processing abilities.

Java Machine Learning Libraries

There are several Java based machine learning libraries that can be deployed to achieve varied level of machine learning tasks with different levels of complexities. The choice of library depends on the type of problem.

Popular Java based Machine Learning Libraries

Popular Java-based machine learning libraries include names like Weka, Deeplearning4j, Massive Online Analysis (MOA), Apache Mahout.

• Weka: is among the earliest and popular libraries, includes wide range of data processing algorithms. Weka is preferred for data processing, classification, regression, cluster analysis. The Weka explorer in Weka provides a Graphic user interface and can be used by developers who don’t have extensive programming knowledge.
• Deeplearning4j: This library of Java is specifically meant for development of deep neural networks and for carrying out tasks like image processing, text processing, and natural language processing and time series analysis.
• MOA (Massive Online Analysis): MOA is open-source designed for manipulating streams of large-scale data. It is primarily suited to handle situations of continuous data arrival like as in real-time analytics and stream mining.
• Apache Mahout: Apache Mahout has been built upon Apache Hadoop and preferred for carrying out tasks like distributed linear algebra. In this library developers can find implementations for various algorithms, including collaborative filtering, clustering, and classification.
• ELKI: ELKI, acronym for Environment for Developing KDD-Applications Supported by Index-Structures, is open-source data mining framework that includes a wide range of clustering, outlier detection, and data indexing algorithms.
• Java-ML: Java-ML with lightweight feature is an out an out Java machine learning library that comprises rich and varied collection of algorithms for classification, regression, clustering, and data preprocessing.
• Smile: Smile Java machine learning library is fast and comprehensive and is preferred for regression, classification, clustering, dimensionality reduction, and other machine learning tasks.