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Isha Dagar
Isha Dagar

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Top 5 languages for Machine Learning

In machine learning, there is no best language as such. Each language is good where it fits best but there are more suitable programming languages that are more appropriate for machine learning tasks than others.

Such as, most of the software engineers use Java for machine learning applications like security and threat detection whereas other prefer to use Python for NLP and LSTM problems. Some also prefer to use R or Python for sentiment analysis tasks. Software engineers with a background in Java development transitioning into machine learning sometimes continue to use Java as the programming language in machine learning job roles.

1. Python : Python leads all the other languages. More than 60% of machine learning developers are using Python and prioritizing it for development because python is easy and versatile to learn.

"While Python has been around for decades, the demand for Python skills in 2022 will continue growing exponentially thanks to its use in the booming industries of data science, machine learning and AI," said Ryan Desmond, co-founder and lead instructor at CodingNomads."In addition, Python is considered one of the easiest, most powerful, and most versatile languages to learn, making it popular amongst companies, developers, and aspiring developers."

Python has many awesome visualization packages and useful core libraries like Numpy, scipy, pandas, matplotlib, seaborn, sklearn which really makes your work very easy and empower the machines to learn.

2. R : R is an open-source programming platform that includes a wide range of libraries and frameworks. Several big tech companies use the R language to run their businesses and with the increasing demand for machine learning and data science in 2021, it is quite evident that R will be in-demand in 2022 and the upcoming years. It is popular in implementing machine learning tasks like regression, classification, and decision tree formation.

3. Java : Java is considered harder to learn than Python but easier than C or C++ because Java is improved on C, and Python is improved on Java. If you learn java then learning something like Python will be much easier. Java provides many good environments like Weka, Knime, RapidMiner, Elka which used to perform machine learning tasks using graphical user interfaces.

4. Javascript : Used on more than 97% of the world's websites, JavaScript allows you to set up dynamic and interactive content, animated graphics and other complex features on the web. It's also the most popular language among contributors on GitHub. Javascript is also so popular in ML that high-profile projects like Google’s Tensorflow.js are based on JavaScript. If you are a master of Javascript then literally you can do everything from full-stack to machine learning and NLP.

5. C++ : C++ has become a go-to programming language for analysts and researchers. Besides it’s popularity in game development domain, many powerful libraries such as TensorFlow and Torch are implemented in the C++ programming language. Therefore C++ and machine learning is indeed a great combination.

Happy Learning.

Top comments (3)

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Logan Kilpatrick

@ishadagar Have you checked out the Julia Language? It is the future of machine learning: towardsdatascience.com/the-future-...

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Pooja Gera

Very well written! Thank-you for this!

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Isha Dagar Author

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