5 Popular Programming Languages for Machine Learning

8 May 2021

Machine Learning is a billion dollar industry where we have seen exponential growth in the last few years, and according to research data on AI Multiple, the market is expected to grow from $1 billion in 2016 to a whopping $9 billion industry by 2022.

Machine Learning Google Trends
Source: Google Trends

An industry with such a huge upside needs programmers who can work on its applications but how exactly can you code machine learning algorithms? There are multiple languages to pursue your career as a programmer in this field.

Some of these languages are extremely popular, such as Python, while others are lesser-known, such as R. So let’s dive into our top 5 programming options to get into machine learning.

Best Programming Languages for Machine Learning

We picked these five languages based on their usage, functionality and popularity in this specific industry:

1. Python

We all know Python as one of the most popular programming languages in the world. The reason behind its popularity is that it has applications in almost all sectors, including app development, gaming and data science.

Over 57% of data scientists use and prefer Python over other languages. The case is the same with machine learning. There are so many dedicated libraries and frameworks that make Python a compatible fit for this sector. The most popular ones include:

  • TensorFlow
  • PyTorch
  • Theano
  • Open CV

Moreover, Python is well-known for its versatility. As mentioned, it is used in many areas, including data sciences and artificial intelligence. With over 8.2 million developers all across the world, python is also one of the fastest-growing programming languages.

Another reason behind the popularity of Python is how easy it is to learn. The syntax is extremely simple and there are no strict procedures for writing code, so it comes highly recommended for machine learning. Remember, however, that Python is not an ideal language for hardware-level apps.

If you are eager to learn more, then join any of these best Python courses to start from the bottom and clear your basic concepts for a bright career.

2. Scala

Scala is popular for its interoperability with Java, as it was actually developed to cover the language’s more criticized points by providing a much better coding experience. Scala covers most of its predecessor’s major flaws while also inheriting many of the advantageous points of Java.

There are numerous uses of Scala in application development and the language is even faster and more efficient than Java. Scala also has an edge over Python because of its compiled structure.

The language is equally efficient in machine learning and developers prefer to use it for large-scale projects. A number of libraries and frameworks are used by Scala for this particular domain, including:

  • OpenNLP
  • MLLib
  • Cortex

Switching to Scala is not a big deal for developers who are already familiar with Java, since Scala uses JVM (Java Virtual Machine) and you can also embed Java code directly into Scala, which highlights the interoperability of both these languages.

You can start your journey by opting for any of these amazing Scala courses.

3. Java

This coding staple receives a lot of criticism due to its flaws but still, it manages to compete in the top programming languages lists. It has numerous applications due to its extensive libraries and frameworks, and moreover, it uses its own JVM to execute the code.

It is a multi-purpose language with a syntax similar to that of C and C++ but the major difference lies in low-level commands that are very limited in Java. Object-oriented programming is a huge upside of Java but still, the code is vulnerable to many small errors that can make the whole application unstable.

The language is highly popular in CRM and ERP systems but it is not exactly optimized for machine learning. The Weka Framework allows machine learning with Java to some extent but large projects are difficult to handle. Here are a few of its other frameworks:

  • Java-ML
  • JSAT

If you are just starting out with Java, then try out these impressive Java courses to have a stronger grip over the language.

4. R

R is the ideal language for statistical computing and many developers also prefer it for machine learning. Both domains, including statistical computing and machine learning are closely related and interconnected in some way.

The language is popular for data visualization and statistical computing but now it’s also expanding to the machine learning sector because of its reliable tools that make data processing easier.

R is not as strong as Python in application development but still, R has a few additional uses in data exploration and prototyping. It also has a few packages specifically to facilitate machine learning, these include:

  • Dplyr
  • Ggplot2
  • kernLab
  • MICE Package

If you are already into statistical computing, then studying this language using one of these best R courses is one of the wisest things to do, especially if you are also interested in machine learning.

5. JavaScript

This is a sort of web-oriented language that works with HTML and CSS to create interactive and responsive web pages. However, JavaScript is much more than that. It has numerous uses in client-side applications and it can also be used on the back-end.

It is also extremely easy to learn, especially if you join JavaScript courses with detailed tutorials to clear the basic concepts.

By using JavaScript for the client-side, we can access the device’s GPS, camera and other sensors with permissions. It is also possible to apply machine learning algorithms by using JavaScript to train how devices behave.

There are numerous libraries and frameworks available that allow machine learning with JavaScript, these include:

  • TensorFlow.js
  • Brain.js
  • Deeplearn.js
  • Synaptic

TensorFlow is the most popular framework for JavaScript to work on such applications, as it allows the use of flexible APIs for building an array of models.


There is no doubt that the Machine Learning domain is going to explode in upcoming years and if you want to be a part of this journey, then you should check out any one of these amazing machine learning courses focused on all the languages we’ve discussed in this article.

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