Scope and Limitations of Java Programming in Machine Learning

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Machine Learning has diversified computer programming in varied ways. With new languages being developed quite rapidly, coding in a particular language might just seem a little laid back. Consider the example with Java developers. With the evolvement of Python and Ruby, Java has lost quite a lot of its initial popularity among coders.

But, though Python or Ruby does have potential benefits in machine learning programs but it is not completely true that Java has become useless. Yes, Java does have limitations which are conveniently fulfilled with these programming languages but the scope of Java is still vast.
Let us take a closer look into the bigger picture to know the future of Java development Services in Machine Learning.


  • Extensive Sphere:

Java has been into the market for years now. There are industries which are developed on Java based tools and applications. Thus, if you are working in an ecosystem where Java has been dominating every system program, it is always worthwhile to stick with the basic.

  • Performance:

Python or Ruby has built a massive social network but when it comes to performance, there is nothing like JVM. By performance we don’t just mean speed of execution of the program, but the program’s implementation time lapse and third party libraries functionality also add on with it.

  • Android Favourable:
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Android mobile apps are all written in Java. Favourable with numerous library functions, Java has become the most simple and convenient programming option for android mobile apps.

  • Convenient Parameter Inputs:

Java Machine Learning libraries offer a varied collection of ML, AI and Data Science algorithm that can be easily implemented to support any domain you want, even without any knowledge of Python or Ruby or any other language.


  • High Memory Consumption:

Java programs runs on Java Virtual Machine. Thus, the memory consumed to execute a Java program is pretty high as compared to other coding languages.

Moreover, the cost of implementation increases with the rise in memory and processing hardware requirement.

  • Programming Limitation:

Unlike Python which is a dynamically typed language, Java uses static syntax rules. Coding with Python gives a special advantage of a reclining option with the use of variables, as the interpreter understands the types and they are checked during run time. But when it comes to Java, the coder has to distinctly declare the variable types, otherwise the compiler will just not recognise them during run time.

Furthermore, languages like python doesn’t follow any indentation rules which makes coding simple, easy to read and write. But in the case of Java, the coder has to clarify the statically typed language and follow the specified indentation rules which makes many experienced coders uncomfortable, especially while writing lengthy codes. You can also buy arduino, Must visit arduino module.

  • Collecting Garbage Data:
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Java doesn’t have functions like Delete or Free which limits the control over garbage collection. Increased garbage collection can lead to memory insufficiency which can affect the programs running time and memory usage.

When it comes to machine learning Python is syntactically pretty easy and empowers the usage of artificial intelligence in their respective domain. But Java is also considered a valuable option for machine learning programs for its easy debugging options and invariant use in large scale applications.

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