There are different aspects to building machine learning (ML) systems. Java is a great programming language that can be used for data manipulations. When we talk about programming languages in the domain of Artificial Intelligence, we know about Python and R as the languages to learn. But many of us don’t know that Java could also be used for ML, AI, or Data sciences. So let’s talk about the significance of Java in artificial intelligence programming used for artificial intelligence programs development.
In this edition, we at Oodles, as an evolving Artificial Intelligence Development Company, shed light on why Java is the star performer for machine learning applications along with some top AI libraries in Java.
AI technology Power is still inconceivable. These technologies can be applied in every industry such as from sales and healthcare to manufacturing and aerospace, bringing significant changes and creating new business models. The AI practical application can be categories in this way as well. For Example: "Service and Products" that includes booking service, medical diagnosis, automotive cars. And the next one is "Process" that includes welding, paintings, assembly robots in the heavy industry, drilling machine in the oil industry, driverless mining trucks in the extraction industry.
a.) Neuroph: Basically it's an open-source framework for neural network creation. More information about this can be available on the Neuroph API documentation.
b.) Deeplearning4j: It is a deep learning library for JVM. It provides different APIs for neural network creation. Tutorials for deep learning and neural networks available on the site of this framework.
a.) Java Machine Learning Library (Java-ML): Basically it is an open-source Java framework that provides different machine learning algorithms specifically for programmers who developed the algorithms to solve the problems.
b.) RapidMiner: It is a platform for data science. It will provide different machine learning algorithms through GUI and through Java API.
c.) Weka: There are many machine learning algorithms. Weka is a collection of different machine learning algorithms, which can be applied directly to the dataset, through the provided GUI or called through the provided API.
Deep Java Library: It is an open-source library that is developed by AWS Labs. It provides an intuitive framework testing learning models and independent Java API for training.
a.) Apache OpenNLP: It is a library that is used in a machine learning algorithm. It is a toolkit for the processing of natural language text.
b.) Stanford CoreNLP: It is a framework to perform NLP tasks.
a.) Jenetics: There is some advanced genetic algorithm. They provide a clear separation of the genetic algorithm concepts which are written in Java.
b.) Watchmaker: To implement genetic algorithms we can use this framework.
c.) ECJ 23: It is a research-based framework. It also supports genetic algorithms. It is developed at George Mason University's ECLab Evolutionary Computation Laboratory.
d.) JGAP (Java Genetic Algorithms Package): It is a genetic programming component, which is used to implement genetic algorithms.
We, at Oodles, are a team of high-performance AI developers building data-driven AI solutions including machine learning, deep learning, and Natural Language Processing. We work with various programming languages such as Python, R, Java, etc. coupled with AI algorithms to automate and streamline critical business processes.
In addition, we are an established Chatbot Development Company offering intelligent chatbot development and integration solutions for global businesses.