Member-only story
Meet Julia: The Future of Data Science
The next big thing, or just massively overhyped?
As a data enthusiast, you have probably heard about Julia, the “future programming language of data science.” There are claims that Julia will replace Python and R in the data science field, as it offers significant benefits in terms of performance, efficiency, and ease of use.
In this article, we will look into what Julia is, its applications, and whether it is worth learning the language for data science.
What is Julia?
Julia was created to offer the simplicity of Python, the statistical capabilities of R, and the speed of C and C++.
Python is a high-level language with a simple syntax that most programmers find easy to use. It allows data scientists to spend less time writing code and focus on model building. Many libraries within Python allow users to build statistical algorithms and perform scientific programming.
However, a major drawback of Python is that it is slow. While it is easy to use and offers a high level of abstraction, the language comes with high latency.
