When one discusses about Machine Learning or Artificial Intelligence; they unexpectedly consider Python or R as a programming language for the resulting execution. But what a large portion of the individuals don’t know is that Java can likewise be utilized for a similar reason. From the business solutions and navigation systems to the mobile phones and its applications it can definitely be told that Java is applicable in nearly every area of technology. Over the last 20 years, Java is one of those languages which is still among the top-ranked and most helpful programming languages used today.
In this blog you’ll understand why one can opt to choose java for machine learning.
JAVA IS VERSATILE
It is possible to use Java across various platforms. It is an open source programming language and is platform independent across OS. It follows “Write Once and Run Anywhere” rule which means you can run Java byte code on any device that has a compliant JVM.
Java is said as one of the most versatile languages, because of its dynamic coding, all codes are stored in an object oriented format known as classes. It can also work with different resources across a network. Hence java programming language is not going out of date anytime soon.
Java is literally everywhere, in desktops, on mobile phones and everywhere else too. It is highly demanded in all the fields for example, it is used in banking to deal with transaction management, in stock market to write algorithms to understand which company to invest in, in information technology to solve and implement real life problems. Hence because of high demand using java for machine learning in these demanding fields makes a lot of sense.
Data science and big data go hand in hand. The most of the popular frameworks and tools which are used for Big Data are written in Java for example Fink, Hadoop, Hive, and Spark.
TONS OF USAGES
Java is also usable in a lot of processes in the field of data science and also data analysis, example in cleaning data, data importing and exporting, statistical analysis, deep learning, Natural Language Processing (NLP), and also data visualization.
Java is also perfectly suited for speed-critical projects as it is known for its fast execution. A lot of popular websites and social applications that are highly used today rely on Java for their data engineering needs, example LinkedIn, Facebook, and Twitter.
LIBRARIES AND TOOLS
Java has a wonderful support community hence learning to code using java is not going to be a problem at all. One has available numerous resources online which can act as a perfect companion, and not to forget it’s support community which is very helpful too. It also has multiple forums, which helps to clear all doubts or errors related to Java are answered.
Scalability is a very important aspect of a programming language that developers usually consider before starting with a project. Java the savior helps in making application scaling a very easy process for data scientists. Scalability is also a reason which makes java a great choice for building large and more complex Artificial Intelligence and Machine Learning applications.
Java is one of the oldest and an incredibly useful, speedy, and reliable language that helps the development cell build a lot of useful projects. From applications of data mining and data analysis to the building of Machine Learning programs, Java is very much applicable in the field of data science. It is one of the most preferred languages for the above tasks. The above mentioned are some reasons to why one can opt java for machine leaning.