There are only around 500 North Atlantic right whales alive today, making them one of the most endangered animals on the planet. Individuals can be identified by photographs taken from vessels and airplanes, and then compared to the North Atlantic Right Whale Catalog run by the New England Aquarium. Knowing the individual identity of a whale opens up many possible avenues of research and conservation management including demographics, social structure, and informed disentanglement operations. The process of matching a photograph to the catalog can be time-consuming, and finding a way to automate this process using the latest in image-recognition technology would free up valuable time and resources so that scientists have more time and energy to devote towards the conservation of these endangered whales. In November 2014, the National Oceanic and Atmospheric Administration (NOAA) contracted with Kaggle, a platform for predictive modelling and analytics competitions, to crowdsource a technology solution. The competition ran from August 2015 through January 2016 with a $10,000 prize pool sponsored by MathWorks, and NOAA Fisheries provided the right whale aerial photographs and associated data set. Data scientists competed to create an algorithm to match a photograph of a right whale to its unique individual identity. The winning solution by software company Deepsense.io relied heavily on convolutional neural networks in their solution to achieve 87% accuracy. This is very different than other approaches to image recognition that typically seek to count the number of individuals in the photograph and classify them to species. This solution actually classifies the whales to their unique individual identity. NOAA plans to use this algorithm to create software to automate the process of identifying whales, thereby freeing up valuable time and resources.