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Julia for Data Science by Zacharias Voulgaris PhD

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Introduction

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I discovered Julia a few years back, and I’ve been intrigued by its potential and its power ever since. Julia’s user-friendly Integrated Development Environment (IDE) made it very accessible, and its high level logic (very similar to Matlab and other high level languages) and performance made it powerful. However, I was more involved in other, more established platforms such as R and Java, and unable to give Julia my full attention.

As such, I didn’t delve much further beyond the basics, including the applications of the tutorial that was available at the time. Besides, I knew that there are constantly new and interesting languages ...

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