Java is a great language for any machine learning project. It can easily be used in this respect for a variety of reasons. To begin with, it is one of the oldest programming languages which means that more people are familiar with it. What is more, it is possible to achieve the desired result in machine learning development faster by using Java. Besides, lots of companies use software that is built on Java. Every year there are new students willing to major in programming. Java remains one of the most popular programming languages. You can easily find lots of useful resources if you need to get more information on this programming language. Students have lots of people to turn to when they need help with Java programming assignment. Another reason why Java will be used in machine learning for a very long time is that the majority of popular Big Data tools and frameworks are built upon Java. As you know, Big Data and data science are a part of a whole when it comes to machine learning. In addition to that, Java is used in a variety of processes such as data analysis, data visualization, data import and export and so on.
Java virtual machine is considered to be one of the best platforms for data science and machine learning. The reason is simple: it gives the programmer an opportunity to write identical code across multiple platforms. Being a strongly typed programming language, it helps to better manage large data applications which is essential for any machine learning project. Data scaling is another vital aspect to take into account. Every programmer knows that scalability is one the best features Java has to offer. When building upon Java, application scaling is going to be a smooth process. What should also be mentioned is that production codebases are typically written in Java code as well. It helps developers figure out how data is generated. Apart from that, it also helps to submit merge requests to product codebases. As a result, deploying machine learning solutions gets easier.
Java machine learning tools
To implement various machine learning algorithms, Java programmers have a variety of tools on hand to make this process faster and easier. Here are some of the most useful ones.
- Java-ML. This is a Java machine learning library, and it’s an open-source framework. It contains a variety of machine learning algorithms that help with data classification, feature selection, data processing and clustering. What is more, it supports files of any type.
- JSAT. This is one of the best Java statistical analysis tools available today. What is more, it has one of the largest collections of machine learning algorithms. Much of this tool supports parallel execution.
- MOA. MOA stands for Massive Online Analysis. It’s another resource that has an open source framework. The available tools enable you to better classify and cluster data, as well as help you with outlier detection and concept drift detection.
- Weka. This is probably the most well-known Java machine learning library. Here you will find tools for data classification, anomaly detection, regression, time series prediction as well as visualization. What is important to keep in mind is that this library is free and very easy to use.
Java is one of the fastest and most reliable programming languages that you can use these days. It can help you create an impressive and effective machine learning project in no time. Besides, it can be applicable in any field of data science or machine learning. Being one of the most commonly used languages, it’s quite obvious that there will be less errors in the process while finding new team members won’t be a problem. If you are going to implement a machine learning project, you should seriously consider using Java.
Why choose Java for machine learning?
When the question of machine learning is raised, the majority believes that either Python or R programming languages are the most appropriate ones. However, it is not always the case, especially considering the fact that Java is just as good as Python or R in regards to machine learning or AI. Here’s why. To begin with, front-end web developers actually prefer Java to other programming languages when the issue of machine learning projects is discussed. 16% of front-end web programmers prioritized Java while only 8% opted for C/C++. What is more, enterprise-focused application developers tend to choose Java for all projects that have something to do with machine learning. What it all boils down to is that there’s no need to learn R, C++ or Python if you already know Java and are about to start working on a machine learning project. You can easily succeed in developing excellent machine learning projects even if you don’t know Python or R. Java is more than enough.
Here’s how your background in Java development can come in handy when you get down to work on a machine learning project. Being familiar with the Java programming language gives you a better understanding of how to develop projects in any data science field. To implement any of the data science algorithms, you can easily use third-party open source libraries. As a Java developer, you shouldn’t have any difficulties with this process. While other programming languages clearly have their advantages, there’s no necessity to spend huge amounts of time learning them if you can easily execute any data science or machine learning algorithms with the help of Java.
What is vital to mention is that Java came into existence a long time ago, yet programmers still use this language for a variety of projects due to its object-oriented nature. Despite the rising popularity of newer programming languages, Java remains one of the most popular languages for AI and machine learning which may seem surprising at first. However, it becomes obvious why Java still proves to be so useful as soon as you start learning it. One can even call it a universal programming language. There’s no doubt that it’s syntax is quite complex. Yet, the reason why so many programmers opt for Java is due to the high speed of execution. Besides, Java is faster than Python. Security is an integral part of any Java design. If you’re creating machine learning solutions, this aspect must be very significant. All in all, Java provides an excellent base for powerful application development due to a variety of rapid development tools. A Java programmer is capable of performing several tasks simultaneously in a program. Combined with efficient coding and debugging, Java is one of the best options when it comes to developing machine learning applications.