Data presented here are subset of a larger plankton imagery data set collected in the subtropical Straits of Florida from 2014-05-28 to 2014-06-14. Imagery data were collected using the In Situ Ichthyoplankton Imaging System (ISIIS-2) as part of a NSF-funded project to assess the biophysical drivers affecting fine-scale interactions between larval fish, their prey, and predators. This subset of images was used in the inaugural National Data Science Bowl (www.datasciencebowl.com) hosted by Kaggle and sponsored by Booz Allen Hamilton. Data were originally collected to examine the biophysical drivers affecting fine-scale (spatial) interactions between larval fish, their prey, and predators in a subtropical pelagic marine ecosystem. Image segments extracted from the raw data were sorted into 121 plankton classes, split 50:50 into train and test data sets, and provided for a machine learning competition (the National Data Science Bowl). There was no hierarchical relationships explicit in the 121 plankton classes, though the class naming convention and a tree-like diagram (see file "Plankton Relationships.pdf") indicated relationships between classes, whether it was taxonomic or structural (size and shape). We intend for this dataset to be available to the machine learning and computer vision community as a standard machine learning benchmark. This “Plankton 1.0” dataset is a medium-size dataset with a fair amount of complexity where image classification improvements can still be made.