Deep learning has revolutionized predictive modeling in topics such as computer vision and natural language processing but is not commonly applied to psychological data. In an effort to bring the benefits of deep learning to psychologists, we provide an overview of deep learning for researchers who have a working knowledge of linear regression. We first discuss several benefits of the deep learning approach to predictive modeling. We then present three basic deep learning models that generalize linear regression: the feedforward neural network (FNN), the recurrent neural network (RNN), and the convolutional neural network (CNN). We include concrete toy examples with R code to demonstrate how each model may be applied to answer prediction-focused research questions using common data types collected by psychologists.

中文翻译：

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深度学习：心理学家入门。

深度学习已经彻底改变了计算机视觉和自然语言处理等主题的预测建模，但并不普遍应用于心理数据。为了将深度学习的好处带给心理学家，我们为具有线性回归工作知识的研究人员提供了深度学习的概述。我们首先讨论深度学习方法对预测建模的几个好处。然后，我们提出了三种泛化线性回归的基本深度学习模型：前馈神经网络 (FNN)、递归神经网络 (RNN) 和卷积神经网络 (CNN)。我们包括带有 R 代码的具体玩具示例，以演示如何使用心理学家收集的常见数据类型应用每个模型来回答以预测为中心的研究问题。