Abstract: A neural network may be trained on a training corpus that comprises a large number of dataset-visualization pairs. Each pair in the training corpus may consist of a dataset and a visualization of the dataset. The visualization may be a chart, plot or diagram. In each dataset-visualization pair in the training corpus, the visualization may be created by a human making design choices. The neural network may be trained to predict, for a given dataset, a visualization that a human would create to represent the given dataset. During training, features and design choices may be extracted from the dataset and visualization, respectively, in each dataset-visualization pair in the training corpus. After the neural network is trained, features may be extracted from a new dataset, and the trained neural network may predict design choices that a human would make to create a visualization that represents the new dataset.