Machine learning has become a global trend in artificial intelligence and computing. Its application cuts across different industrial verticals. The application of machine learning algorithms in material science and related fields is becoming a topic of interest to many researchers. However, unlike other fields such as health, sports, communication, and agriculture, the use of machine learning in material science is still in its ideation stage. This mini-review is designed to explore some of those machine learning tools that have been applied to material science, the importance of machine learning in material science, and the challenges limiting the implementation of machine learning techniques in material science. One of the major findings from this review is that the limited availability of material science data is a major challenge to the implementation of machine learning algorithms. A specialized material science data repository was recommended.
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