6 Best Programming Languages in Machine Learning You Can Learn for 2021

6 Best Programming Languages in Machine Learning You Can Learn for 2021

Programming languages could be your career shield, especially for any technical job role. While machine learning and artificial intelligence (AI) have become among the most sought-after technology by potential employers, knowing what programming language to learn is a must-have.


From theoretical studies to the academic world and practical application, machine learning plays a significant role. However, choosing which best programming language that could be perfect for machine learning can still be a challenge.


Most AI and machine learning specialist have their own set of preferences when it comes to choosing the language, yet the current usage or practical application of a certain programming language could vary from one programming language to another.


Choosing one particular programming language could be unfair. Therefore, we will allay your fear of confusion and list down the top programming languages ideal in machine learning.

  1. Python

Python programming has always been a leader amongst the programming languages. One of the best reasons is due to its easy usage and simple syntax. This language has centered itself around data science and machine learning and is used by major leading experts in the field. It has been positioned as a greater choice for data scientists and AI professionals due to the arrival of TensorFlow and other multiple libraries.


Not to mention, this programming language has been a popular choice amongst amateurs entering the field. More so, developers and programmers can choose their preferred Python libraries based on the projects they’ll be working with. For instance, Keras, Teano, and scikit-discover are ideal for AI, NLP, and deep learning.

  1. Java

The second most preferred programming language in machine learning is Java. Most data scientists and machine learning experts along with nearly 15 percent of specialists have used Java for detecting cyber-attacks, fraud detection, and network security. Java is used where Python was the least preferred choice for the task.


Java is easy to use, has better user interaction, and is perfect for large projects. Also, it has machine learning algorithms that have been composed in Java.

  1. R

Although R is a preferred choice for data visualization and statistics, it can also be the right choice for anyone seeking to grasp mathematical computations related to machine learning. More so, the R programming language beats Python in terms of visualization and data analysis.

This language can facilitate prototyping and help assemble your ML models. R can act as a great supporter of your ML pursuits.

  1. JavaScript

JavaScript is the most common web scripting language and has the perfect libraries that can be used for training and deploying ML models like machinelearn.js, math.js, R-js, TensorFlow.js, stdlib-js, Brain.js, and face-api.js.

  1. Lisp

Lisp is considered the second-best programming language that is yet to be used. This programming language is steered toward dealing with projects related to AI development. Lisp is known for its flexibility thus can also be called extremal. It offers endless opportunities to coders like domain-specific programming language that is embedded within the code and building proprietors.

  1. Shell

Shell is almost similar to Python and it also offers basic and smooth syntax. However, this programming language could still be an amateur language by users seeking to get deeply engaged in machine learning development. Owing to its speed, this programming language can perform a task within seconds for a task that might normally take ten minutes through the graphical interface.

Some of its best machine learning libraries include Docker-prediction, MI-Notebook, and DI-Machine.

Besides these programming languages, you can also add TypeScript, Julia, Scala, and C++ for machine learning.


Python, R, and JavaScript are training in the data science and machine learning world. Thus, having knowing multiple programming languages could be an added advantage to your ML career.