Introduction

Over the past ten years, the scientific computing craze has escalated further and further, and with that so have the great options available to programmers for mathematical computation and data manipulation. One of the languages that might not be as popular as other languages in the field, like Python and R, is an open-source, multi-paradigm, and incredibly dynamic language called Julia.

Julia is a language that was created to be not only used in general-purpose applications, but also be very geared towards scientific computing and computational analysis. While this in and of itself means that Julia might be better for those applications than languages that are not built to do these operations, there are also a lot of really neat attributes that the language holds that make it great for scientific computing aside from just being built to do it.

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