Comprehensive Guide On Java Tools for AI and Machine Learning

Sanam Malhotra | 6th April 2020

Among programming languages, Java is recognized as the most rewarding language that “strives for perfection”. In light of artificial intelligence (AI) and machine learning (ML), Java is propelling innovative and expansive solutions for enterprises. As a well-positioned provider of artificial intelligence services, Oodles AI has employed multiple Java tools for AI including Hadoop, Apache Spark, Scikit-learn, etc. Here’s an elaboration of how Java dominates the future of AI and various Java tools for enterprises aiming to adopt AI.

 

Java: The Future of AI and Machine Learning for Enterprises

Enterprises, whether emerging or established, denote Java as the cornerstone of their digital architecture. Touted as the “enterprise language”, Java is the oldest and most widely used programming language that is ruling the software industry for 20 years. From big data to artificial intelligence and cloud machine learning solutions, Java exhibits great potential to run and deploy expansive business applications.

In a presentation at Oracle Code One 2018, Bernard Traversat, Head of the Java platform development, elaborated the future of Java tools for AI and machine learning by stating,

“One of the strong positions that Java has in the Big Data space is that all the open-source Big Data stacks are either written in Java or have been written for the Java Virtual Machine.”

Java tools for AI

 

In addition to support from big data stack, Java constitutes an enormous ecosystem of tools and libraries that empowers enterprises to-

a) Embed AI and ML technologies easily into the business models

b) Practice massive data scaling up to multi-terabyte heaps

c) Achieve significant competitive edge with exceptional language performance

d) Maintain cost-efficiency and low latency

Also read- Applying Sentiment Analysis on User Feedback with Java

 

Top-notch Java Tools for AI and Machine Learning

1) Weka

Weka is a standard Java tool for practicing machine learning and integrating trained ML models into Java applications. It is an open-source ML software that can be accessed through a Java API or GUI. Weka supports wide-ranging built-in tools such as scikit-learn, R, and Deeplearning4j.

Under machine learning, Weka can be used for both supervised and unsupervised learning wherein it renders the following tasks-

a) Data Cleansing and preprocessing

b) Classification and regression systems

c) Data labeling

d) Building a decision tree

e) Data Visualization

Weka java tool for AIThe interface of Weka explorer being used for supervised learning. 
Image source- Mark Watson research

By constituting ML techniques, Weka brings the following advantages to a business application-

a) Compatible with modern computing platforms

b) Easy to deploy

c) Scalable for new machine learning projects

 

2) Eclipse Deeplearning4

Eclipse Deeplearning4j is a distributed deep learning library written for Java and Scala (a JVM language). With seamless integration of Hadoop and Apache Spark, Deeplearning4j enables businesses to embed AI technologies into their infrastructure efficiently.

One of the most prominent Java tools for AI, Deeplearnign4j fosters a secure environment via Kerberos for-

a) Connecting multiple data streams

b) Cleaning data

c) Building vectors for neural networks

d) Fine-tuning neural networks

e) Deploying deep learning applications via REST, Spark, Android, or Raspberry Pi environments.

Also read- How AI development with Raspberry Pi 4 Empowers IoT Applications

 

3) IntelliJ

In the words of professional developers, Intellij is the ultimate Java Integrated Development Environment (IDE) for machine learning. In its 202 Roadmap, JetBrains, the parent company of Intellij IDEA, is eyeing to host additional machine learning-based code completion capabilities.

With IntelliJ, businesses can perform the following machine learning tasks-

a) Improving the ranks of completion variants

b) Language plug-in tags

c) Identifying attributes that contribute to item ranking

d) Contextual ranking completion suggestions, and more

Also read- Deploying Machine Learning for Android Applications Development

 

Deploying Java Tools for AI and Machine Learning with Oodles AI

Oodles AI is an emerging AI development Company that houses a well-experienced AI team that develops enterprise-scale machine and deep learning solutions. We have hands-on experience in deploying Java tools for AI and machine learning including-

a) Hadoop

b) Apache Spark

c) Apache Kafka

d) Deeplearning4j

e) Scikit-learn, and others

We develop cutting-edge AI-powered Java applications for businesses to augment their capabilities and gain a competitive edge. To learn more about our AI development services, reach out to our AI development team.

About Author

Sanam Malhotra

Sanam is a technical writer at Oodles who is currently covering Artificial Intelligence and its underlying disruptive technologies. Fascinated by the transformative potential of AI, Sanam explores how global businesses can harness AI-powered growth. Her writings aim at contributing the multidimensional values of AI, IoT, and machine learning to the digital landscape.

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