In this tutorial review, we will describe crucial aspects related to the application of machine learning to help users avoid the most common pitfalls. The examples we present will be based on data from the field of molecular electronics, specifically single-molecule electron transport experiments, but the concepts and problems we explore will be sufficiently general for application in other fields with similar data. In the first part of the tutorial review, we will introduce the field of single-molecule transport, and provide an overview of the most common machine learning algorithms employed. In the second part of the tutorial review, we will show, through examples grounded in single-molecule transport, that the promises of machine learning can only be fulfilled by careful application. We will end the tutorial review with a discussion of where we, as a field, could go from here.

中文翻译：

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信任我们的机器：验证用于单分子运输实验的机器学习模型

在本教程回顾中，我们将描述与机器学习应用相关的关键方面，以帮助用户避免最常见的陷阱。我们提供的示例将基于来自分子电子学领域的数据，特别是单分子电子传输实验，但我们探索的概念和问题将具有足够的普遍性，可以应用于具有类似数据的其他领域。在教程回顾的第一部分，我们将介绍单分子运输领域，并概述最常用的机器学习算法。在教程回顾的第二部分，我们将通过基于单分子传输的示例展示机器学习的承诺只能通过仔细应用来实现。我们将通过讨论我们在哪里结束教程回顾，