Dynamically triggered earthquakes and tremor generate weak seismic signals whose detection, identification, and authentication call for a laborious analysis. Citizen science project Earthquake Detective leverages the eyes and ears of volunteers to detect and classify weak signals in seismograms from potentially dynamically triggered (PDT) events. Here, we present the Earthquake Detective data set - A crowd-sourced set of labels on PDT earthquakes and tremor. We apply Machine Learning to classify these PDT seismic events and explore the challenges faced in segregating such weak signals. The algorithm confirms that machine learning can detect signals from small earthquakes, and newly demonstrates that this specific algorithm can also detect signals from PDT tremor. The data set and code are available online.