Top 5 Machine Learning Libraries for Java You Should Know About

Skills in machine learning are hot in trend as more and more companies are looking for programmers who have a good knowledge of ML. As everyone knows that Java is one of the most famous programming languages and no one apart from Python has won its position. Nowadays, Java has become the standard programming language to implement ML algorithm. There are 7 facts of Java language, as it is the software lead by examples. Well, here is the list of the best machine learning libraries for java. Students who are writing an assignment on the topic may need Java assignment writing help to mention the following libraries in their task.

  1. Weka: Well here comes our first Java machine learning library. It is no surprise that Weka is the first on the list. It is the fully Java-based machine learning library that is used for recording the ML algorithm. Apart from the ML algorithm, Weka is also used for data mining, predictive modeling and data analysis. In addition, it is completely free, portable and easy to use. As per the prof. Eiba Frank “the strength of Weka comes from the classification so, applications that require classifications of data can use it for effective result”
  2. MALLET: The second ML library on the list is Mallet. The full form of term MILLET refers to the machine learning for language toolkit. This Java-based ML library supports the statistical nature and can be used for statistical NLP, document classification, topic modelling and other machine learning applications. Unlike most of UL library, it supports a wide range of algorithms including decision trees, Naïve Bayes and maximum entropy.
  3. ELKI: - ELKI is a Java-based machine learning library specially designed for researchers and designers. It is also an open-source data mining software and provides a large number of highly recommended algorithm parameters. It is highly used by graduate students who are looking for a way to make sense out of their datasets. Designed and developed for researchers and students, it is the knowledge-based database framework aim to deliver advanced database algorithm. Students can take Java essay writing help from BookMyEssay to properly mention this software in their assignments.
  4. Massive online analysis: - If you have ever used massive online analysis then you are probably become the fan of this machine learning library. This open-source Java-based software is highly recommended for machine learning and data mining. It is developed in Java and you can use it with the Weka without any trouble. If you search through its history then you find that it is used in the data science community for regression, classification, clustering and other recommended applications.

 The main reason why it is highly suggested for IoT devices is that it contains a large collection of ML scales which can be used while handling massive data.

  1. Deeplearning4j: - the last but not least ML library on the list. Just like all above libraries, it is also written for Java. The deeplearing4j serve as a DIY tool in the Java. Considered as one of the best software in Java ecosystem it has an ability to handle several limitless concurrent tasks.

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