Machine learning (ML) involves writing codes that help computers make decisions based on instructions called algorithms. It’s the wheel behind artificial intelligence (AI) and the use of AI continues to grow fast, creating more opportunities for machine learning programmers. If you’re interested in learning a new programming language, you’ll face your first dilemma quickly: choosing a programming language. For most newbies, this might be challenging. Multiple languages can create machine learning codes. Yet, you can’t learn all of them. Here’s the best part, though: to get your start as a programmer, you only need to study one language.
But how do you choose from among many high-level languages? First, you must identify what you want to build. Then select a language that’s easy to learn, flexible, and has extensive libraries. Still unsure? No worries; we’ve selected 2023’s most popular programming languages to help you narrow down your search.
Python
Over the years, the use of Python has been growing steadily, overtaking popular languages like Java, C, C++, and C#. Currently, Python ranks as the most demanded programming language based on job advertisements in the U.S. and is also GitHub’s preferred programming language.
Python uses one of the most natural languages and less complicated syntax and is easy to learn, read, and correct errors with. Best of all, Python is an open-source language, meaning it’s free to access and distribute. As a result, it has versatile libraries.
Python’s libraries
A library is a collection of modules or codes made to perform specific operations. Some modules can help with the graphical user interface, data analysis, and graphs, among other things. Instead of writing the same code every time you need it, you can import it from the library.
This library simplifies the work of a programmer, making accessing information fast and convenient. Considering that Python has one of the largest online support communities, you can access many modules for use in any program you want to write.
This language is helpful in the booming industries of data science, artificial intelligence, and machine learning. Due to this application, Python is likely to be in high demand in the future. It’s also popular in web-based applications and can be used to develop mobile and desktop applications.
JavaScript
The second most preferred language on GitHub, about 95% of all websites use JavaScript, including top companies like Google and Netflix. This text-based language is not open-source, but it’s free to use.
It helps create interactive web pages both on the client-side and the server-side. Some of the things you can do with it include creating 2D/3D animated graphics, websites, presentations, web applications, art, games, and so much more. You can also use it to make non-web apps such as mobile and smartwatch applications.
JavaScript is highly compatible with many operating systems and browsers and web browsers can interpret JavaScript, meaning there’s no need for a compiler. It comes with many useful functions that you can reuse every time you need them, such as codes for finding the time and date and validating online forms.
You can do much more with JavaScript by using its enormous libraries. These libraries contain codes made for specific and often complex operations, simplifying your work and eliminating the need for an in-depth study.
R
R is an open-source programming language used for statistics and is the best alternative to traditional languages like Stata, SAS, and SPSS. R helps visualize statistical data by use of graphics and is used by large companies such as Google and Facebook. As an open-source software, you can download and use it for free.
When it comes to advanced statistics, R is quite ahead of Python. Python is a general-purpose programming language that adopts a general approach to statistics; R is capable of in-depth statistical analysis. However, there’s a catch: R is much harder to learn than Python.
Some of the applications of R include data mining, time series analysis, regression analysis, stock-market modeling, risk assessment, and simulation. Also, R is helpful for organizations that need to collect and analyze customers’ data, like healthcare, e-commerce websites, social media, and finance.
Java
Java is the third most used language on GitHub. This object-oriented programming language is an improvement of C and C++, eliminating the errors that occur in C and C++. It’s also easy to learn, considering it’s a high-level language with simple syntax.
Java codes comprise methods and classes. Methods are blocks of codes that execute when called; a collection of methods makes a class. Java’s motto is write once, run anywhere; this means you can run it on any machine, making it one of the best programming languages.
Some of Java’s features include exception handling and garbage collector; its applications include mobile apps, web, games, GUI, and embedded electronics.
C++
C++ is a general-purpose, powerful, and widely used programming language. It’s a multi-paradigm programming language, meaning it can use procedural, functional, and object-oriented programming approaches. It’s also a middle-level language, boasting features of both low-level and high-level programming languages.
C++ is used to create various applications especially for business uses, such as Microsoft Office. You can also use it to build games, operating systems, and browsers, among many other applications. C++ apps are fast and can run on various platforms like Windows, Mac OS, and Linux.
Choosing the Right Machine Learning Language
The five languages highlighted above are currently the best options for machine learning, however, it’s easier to focus on one language and become an expert before diving into another. R and JavaScript are specialized languages, perfect for statistics and web development, respectively. Python, C++, and Java are general-purpose programming languages, used to build almost any app.
If you want to build your career in any of these machine learning languages, Ironhack is here to help you. Our Web Development Bootcamp offers flexible study modes, including remote, on-campus, full-time, and part-time courses. Come and learn with experts and before you know it, you’ll be building the career you love.
