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A new toolkit goes beyond existing machine learning methods by measuring body posture in animals with high speed and accuracy. Developed by researchers from the Centre for the Advanced Study of Collective Behaviour at the University of Konstanz and the Max Planck Institute of Animal Behavior, this deep learning toolkit, called DeepPoseKit, combines previous methods for pose estimation with state-of-the-art developments in computer science. These newly-developed deep learning methods can correctly measure body posture from previously-unseen images after being trained with only 100 examples and can be applied to study wild animals in challenging field settings. Published today in the open access journal eLife, the study is advancing the field of animal behaviour with next-generation tools while at the same time providing an accessible system for non-experts to easily apply machine learning to their behavioural research.