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Machine learning is driving development across many fields in science andengineering. A simple and efficient programming language could accelerateapplications of machine learning in various fields. Currently, the programminglanguages most commonly used to develop machine learning algorithms includePython, MATLAB, and C/C ++. However, none of these languages well balance bothefficiency and simplicity. The Julia language is a fast, easy-to-use, andopen-source programming language that was originally designed forhigh-performance computing, which can well balance the efficiency andsimplicity. This paper summarizes the related research work and developments inthe application of the Julia language in machine learning. It first surveys thepopular machine learning algorithms that are developed in the Julia language.Then, it investigates applications of the machine learning algorithmsimplemented with the Julia language. Finally, it discusses the open issues andthe potential future directions that arise in the use of the Julia language inmachine learning.

Julia Language in Machine Learning: Algorithms, Applications, and Open Issues