In this review article, the latest applications of machine learning (ML) in the additive manufacturing (AM) field are reviewed. These applications, such as parameter optimization and anomaly detection, are classified into different types of ML tasks, including regression, classification, and clustering. The performance of various ML algorithms in these types of AM tasks are compared and evaluated. Finally, several future research directions are suggested.

中文翻译：

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增材制造中的机器学习：回顾

在这篇评论文章中，回顾了机器学习 (ML) 在增材制造 (AM) 领域的最新应用。这些应用程序，例如参数优化和异常检测，被分为不同类型的 ML 任务，包括回归、分类和聚类。比较和评估了各种 ML 算法在这些类型的 AM 任务中的性能。最后，提出了几个未来的研究方向。