Top 10 reasons why you should learn Java Machine Learning

When it comes to machine learning and data science, young programmers often suggest Python and R language. However, an experienced IT professional recommend Java machine learning or Java for data science. It is a hard argument to say which one is the best programming language for machine learning or data science.

Nonetheless, Java is used by many professionals for data analysis and machine learning projects. Since the early 21st century Java is a dominant programming language adopted mainly in many companies. It is highly unlikely to lose its popularity just because many competitors are coming up at the market.

Besides being an open source programming language, Java frequently updates itself to make it compatible with the trending technology. The recent release of Java updates comes with many machine learning tools and java machine learning library to support machine learning and data science computation easily. Some worth mentioning Java machine learning tools are Deeplearning4j, Weka, Java-ML, and MLlib. Since the Java platform is used to establish many enterprises, there is also a significant demand for developers and data scientist with Java knowledge. However, it may be difficult for beginners to master Java machine learning and Data science; it is worth learning it.

Here are 10 reasons how Java facilitates Machine learning-

1. Easier to find experts with Java skills.

Machine learning application requires a large amount of data as input. Java was used to develop most of the famous Big Data frameworks such as Hive, Spark, and Hadoop. It is easier to find developers with Java skills and work with either Java for data science or Java machine learning projects.

2. Java machine learning library.

Java has a significant number of machine learning libraries and tools for data analysis. To mention some popular tools and libraries used to solve ML or data science problems are Weka machine learning, MLlib, Deeplearning4j, and more.

3. New updates with every released version.

Java regularly releases new updates bringing the better version of itself to support future technologies. Java 8 has Lambda Expression to rectify most of Java’s verbosity. JDK 9 has the most awaited tool, JShell or REPL (Read-Evaluate-Print-Loop) for developers to code, execute, and then continue to evolve the code at the moment without a need to exit and run a build and so forth.

4. Java is Strongly Typed.

Type safety is an essential feature while developing a machine learning algorithm dealing with extensive data. As Java is strongly-typed it ensures developer are clear about the types of variables and data they declare.

5. Java runs at JVM.

JVM supports the broadest range of programming languages that have similar syntax. It allows the developer to build custom tools quickly and improve developers’ productivity. Some of the popular programming languages are Scala, Java, Groovy, Jython, Clojure.

6. Java developer can quickly master Scala.

Scala is a programming language that runs on JVM. Scala is used extensively for data science and Machine Learning, and it gets more comfortable if you already know Java programming. Spark framework facilitates a Scala programmer analyzing data and build applications that work with streaming data.

7. Java is highly scalable.

The scalable characteristic of Java has made it a great choice when it comes to building an extensive and more sophisticated machine learning projects. Developer favour Java programming if they want to develop an application for scratch which requires scalability in the future.

8. Faster responsive application.

Speed is an important parameter to consider when it comes to developing a large-scale machine learning project. Compared to other regularly used languages for machine learning, Java has an ideally faster response. MNCs like Facebook and Twitter use Java for data engineering. Java also supports concurrency, which adds to a quicker response.

9. Java experts have the highest number of hiring.

When it comes to the highest number of Job openings, Java skillset has the highest demand. It means Industries still require Java developer and in turn the need for more Java machine learning engineers. If you have Java skills you are more likely to get hired quickly.

10. Easier to invest in Java Machine Learning developer.

From the early release of Java, various Industries have adopted it for developing their business.  It’s quite likely that most organization has a significant part of their infrastructure based on Java. A company finds it more manageable when the employee knows Java Machine Learning or train their Java developer in Machine learning.


    1. This information is very useful for me. Thank you for sharing.

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