MACHINE LEARNING PROGRAMMING IN JAVA
Before reading this article take a moment and look around you. What do you see? Do you see gadgets around you with virtual personal assistants, social media platforms, image and speech recognition, google maps, google translate? Well we all know that how these things have made our lives much easier and effortless. All these things are possible because of machine learning which is flourishing at an exponential rate.
Do you know what is machine learning?
Machine learning is a type of artificial intelligence that allows software applications to learn from the data without human assistance and adjust actions accordingly or it is a process of teaching a computer system how to make accurate predictions when fed data. Interesting right?
Are you interested in including machine learning algorithms in your current application? But the confusion occurs when you start selecting a programming language for the same. When we talk about machine learning we spontaneously think of python as programming language for the subsequent implementation. So, in this article we will explore another programming language which is java and we will see that how it fairs against python.
Java is a general-purpose programming language, created in 1995. It is platform independent and object oriented. Well optimized java code is nearly as fast as lower-level languages like C++ and much faster than python, PHP, etc. In the world of programming java is one of the oldest and reliable programming languages.
Let’s list down some advantages of using java code-
· Java development tools. For example-Netbeans, Intellig, Eclipse.
· Java is an object- oriented programming language.
· Java is versatile
As we have listed down some of the advantages of java code, let us move on to the most important section of this article.
Libraries for implementing machine learning in Java-
To implement machine learning in java there are various open source libraries available in java. Let us check the most common ones.
JavaML
It is a collection of machine learning algorithms and has a common interface for each type of algorithms. Software engineers and programmers can gather plenty of code samples and tutorials. The reference implementations of algorithms in this library are described in the scientific literature and a source codes are properly documented. Some of its features are-
· Classification
· Databases
· Clustering
· Data manipulation
· Feature selection
· Documentation
ADAMS
It stands for advanced data mining and machine learning systems. It is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes and it also offers a wide range of operators that perform retrieval, processing, mining and visualization of data. Some of its features are-
· Streaming and scripting
· Databases
· Visualization
· Data processing and documentation
· Machine learning/ Data mining etc.
Deeplearning4j
Eclipse Deeplearning4j is the first commercial grade, open-source, distributed deep-learning library written in java for the java virtual machine. It has an advantage of the latest distributed computed frameworks such as Apache spark and Hadoop. Its features are-
· Sample projects in multiple languages
· Commercial-grade and open-source
· Brings AI to business environments
· Detailed API doc
WEKA
It stands for Waikato Environment for Knowledge Analysis. It has a lot of machine learning algorithms and it also supports deep-learning. Also, it is a free, open-source and easy machine learning library for java. It focuses on-
· Tools and dada preparation
· Classification and regression
· Data mining and clustering
· Visualization etc.
Mahout
It is a distributed linear algebra framework and mathematically expressive Scala DSL to let statisticians and data scientists to quickly implement their own algorithms. It also supports multiple distributed backends (including Apache Spark).
· Scalable performant machine learning apps
· Recommendation systems
· Classification and clustering
As we have explored all these libraries for machine learning in java, we can now say that java is no less than python. The codes in java runs faster than python as it is a compiler-based programming language where python is an interpreted based language. Another problem in python is its memory consumption, it is hard to perform any memory intensive tasks in python. Fixing bugs in python is complex as it leaves objects vulnerable to mutation. Whereas in java object mutation is impossible.
Both the languages have their unique features and qualities. Python on the other hand is very versatile with abundance of libraries and frameworks. Its simple syntax and readability promote rapid testing of complex algorithms and makes it easy for the non- programmers. Also, python has a lot of great API’s that allows to make AI’s quite easily.
Java is a more complex language if we compare it to python and requires changes when runs on older platforms. There’s no doubt that python is the most emerging language in this field and is a best choice for the beginners. Machine learning is a new way of communicating your ideas and thoughts to a computer. So, try and explore as many languages as you can which will definitely help you grow in this field.
