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Due to groundbreaking strides, we now possess rich data sources to help us build models using Artificial Intelligence (AI) that solve complex real-world problems. As a result, Machine Learning has seen an upsurge in popularity and is one of the most rapidly expanding fields of computer science in recent times. This subset of AI is centered on the use of datasets and mathematical algorithms to enable the system to make decisions without manually written code or having been explicitly programmed.

When it comes to selecting a programming language to write Machine Learning based programs and applications, there is a large array of options. However, each programming language has its ups and downs. Since writing algorithms from the ground up can be a laborious endeavor, selecting a language that best caters to one’s needs is vital. The programming language that is most ideal comes with ready to use prebuilt repositories and possesses advanced data science and data model support.

Here are some of the best programming languages available for Machine Learning.


Python is one of, if not the most popular programming languages for Machine Learning and is one of the first languages that got the support of machine learning through its wide assortment of frameworks and libraries such as TensorFlow, NumPy, SciPy, Keras, Scikit and Teano. The reason for its popularity is due to its incredibly simple syntaxes, which makes it ideal for beginners. It is also very popular among data scientists and Machine Learning engineers, as 57% of them according to one survey, have selected it as their primary programming language.


With just over 9 million Java developers worldwide, Javascript continues to be the most popular web scripting programming language. From being a language chiefly used in web development to one that encompasses all facets of computer programming, Javascript has made considerable forays into Machine Learning due to TensorFlow.js – an open source repository used to develop Machine Learning models completely and directly in our web browsers. For uninitiated developers new to data science and machine learning who are looking to build enterprise centered applications, Javascript is a good option as it allows them to visualize algorithms via web-based dashboards.


Despite Python overtaking Java as the most preferred programming language, its popularity has not fallen over the years. This accessible language already has a multitude of Machine Learning frameworks such as Weka, Massive Online Analysis, ADAMS, JavaML and Mahout, to name a few. With such flexible repositories, Java is well adapted to enterprise environments where developers can build Machine Learning systems with great momentum, precision and efficiency. Even the newest as well as past Machine Learning algorithms are still written in Java thanks to it being an extremely safe programming language as it employs bytecode and sandboxes for verification before making any execution.


R is a cross-platform dynamic, object-oriented, array-based and functional programming language that has increased in popularity with data scientists, statisticians and machine learning engineers due to its functional and statistical algorithm capabilities. R is a graphics-based language that was developed with statistics, analysis and data visualization especially in mind and has an incredibly active open source community that continues to keep the language up to date. Although it is more difficult to create Machine Learning algorithms using R, developers are able to create statistical visualizations of those algorithms, making it an excellent complementary language for those looking to explore statistical data with graphs.


In the end, it would be unfair to crown any programming language for machine learning as the “best” or “most ideal” across the board as specific developments require specific technologies. What it actually comes down to is what a developer is looking to create. Each programming language has its unique advantages and this is why developers should always choose what best fits their development strategies and outcomes.

Most machine learning developers in general may lean towards choosing Python as their favored option because of its vast libraries and comparative simplicity of use while enterprise level developers would prefer using Java as their primary programming language. Ultimately, whatever language a developer chooses, it is all about creating future Machine Learning offerings that gets to benefit everyone.