Can JavaScript be Used for Machine Learning?

What is JavaScript, anyway?

JavaScript is a high-level object-oriented programming language which, along with HTML and CSS, serves as a backbone for the World Wide Web. The language supports asynchronicity, along with functional and imperative programming paradigms. If you don’t know what any of that means–it’s basically able to deal with different styles of programming and server-side work. Almost every website you see on the web uses JavaScript; if it is dynamic, with smooth transitions and automated component behavior, then it likely uses JavaScript to do so.

JavaScript is an extremely powerful language which can be embedded directly within HTML, and allow for a website to go from a static and boring series of linked pages to an interactive and immersive web experience.

Lately, JavaScript has seen an explosion in popularity, with sophisticated frameworks such as Node.js and Angular.js, and not to mention the ever-so-popular React.js, taking over front-end development. Especially in the case of React, JavaScript has been innovating cross-platform web, mobile, and application development. The community is becoming so big that even machine learning is seeing a burgeoning community of JavaScript practitioners, using and contributing to massive open-source projects such as Tensorflow.js, MachineLearn.js, and Brain.js, just to name a few. Even though Python still remains by far the most popular framework for machine learning in industry, JavaScript has its own niche special advantages, which we will describe in the last section. But first, let’s explore some context on the pros and cons of JavaScript as a language.

Can JavaScript be Used for Machine Learning

The Advantages and Drawbacks of JavaScript

As mentioned in the introduction, JavaScript has a ton of advantages that both come with and justify its popularity; and its popularity is, in fact, one of them! The ubiquity of JavaScript in the industry means that support forums and tutorial platforms flourish with helpful and experienced developers who like to help newcomers through their initial struggles. From YouTube tutorials to StackOverflow posts to blogs (like this one!), you know there are a variety of resources from which you can get over your current hurdle in learning the language.

JavaScript is popular for a reason; its multi-paradigm capability makes it a great candidate for dynamic web programming. Since it has the first-mover advantage, having grown up with HTML and CSS through the early stages of the Internet, it has remained the web standard in terms of powerful web programming languages. In the time that JavaScript has existed, the community has grown and contributed so much on top of the functionality of the language itself. Frameworks like Node, Angular, and React use JavaScript to elevate both front- and back-end web development. If you plan on being a web developer of any kind, it is essential that you learn the language; the HTML/CSS/JavaScript stack is the “bread and butter” of the Internet. All of the great interfaces and frameworks that the JavaScript community has created makes it easier than ever to create beautiful, dynamic, and interactive websites and cross-platform applications. JavaScript brings websites alive through automated changing of any web component or variable, like transitions, color changes, pretty animations, and effects, etc.

Another advantage of JavaScript is its speed. Since JavaScript is an interpreted language (like Python and Ruby) and is executed on the client-side, this saves server communication times and means that scripts can run significantly faster than compiled languages such as C++ or Java.

However, JavaScript has its drawbacks. One of the biggest drawbacks is the lack of client-side security. Since, as aforementioned, JavaScript is interpreted and executed on the client-side, it is entirely readable and even adjustable by the user. If you have any important information or sensitive functionality in your scripts, a malicious actor could easily get their hands on it or ruin it. In order to add more security to the client-side, JavaScript does not allow reading or writing to files, which is also a drawback of its own.

Another con of the language is that it does not support multiple inheritance. In object-oriented programming, it is sometimes fitting to represent an object as inheriting from two or more parent objects. Whether or not you agree with the use of multiple inheritance, JavaScript will not even allow you to if you wanted to.

JavaScript also does not support multi-threading. Multi-threading allows one to execute multiple “threads” or sequences of code at the “same time” (by alternating between them rapidly). If you intend to run multiple processes on different threads, JavaScript is not the way to go.
Finally, JavaScript is not a popular language for machine learning, as we will discuss in the final section.

Should You Use JavaScript for Machine Learning?

Though the JavaScript machine learning frameworks mentioned in the introduction of this article do, in fact, have growing communities championing their development and uptake, Python remains the industry standard for machine learning. Just as JavaScript has the first-mover advantage as the language of choice for web development alongside HTML and CSS, Python has the first-mover advantage as the language of choice for data science and machine learning. Having many of the same advantages of JavaScript, but with additional simplicity and readability, Python takes the cake when it comes to modeling and predicting from data. Tensorflow, Keras, PyTorch, NumPy, Scikit-Learn, Matplotlib, Pandas, and many other Python packages are each massive open-source projects with hundreds of monthly contributors and a ton of support. Although you can definitely use JavaScript to investigate and model data, if you plan on getting a job in the industry focused on data science and machine learning, you must have a good handle on Python.

JavaScript may have its advantages for machine learning, however. If you already have a good handle on web development in JavaScript and want to explore data and machine learning through web applications, then JavaScript is a fine way to go. Since it’s now a general-purpose cross-platform and full-stack capable language, JavaScript is an entirely valid language to use for machine learning. Carefully consider your goals, pick whichever language seems to fit best, and stick with it! You can always learn the other later on, once you have a good foundation in the basics.

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