Galah is an ongoing high-resolution spectroscopic survey with the goal of disentangling the formation history of the Milky Way, using the fossil remnants of disrupted star formation sites which are now dispersed around the Galaxy. It is targeting a randomly selected, magnitude limited ($V leq 14$) sample of stars, with the goal of observing one million objects. To date, 300,000 spectra have been obtained. Not all of them are correctly processed by parameter estimation pipelines and we need to know about them. We present a semi-automated classification scheme which identifies different types of peculiar spectral morphologies, in an effort to discover and flag potentially problematic spectra and thus help to preserve the integrity of the surveys results. To this end we employ a recently developed dimensionality reduction technique t-SNE (t-distributed Stochastic Neighbour Embedding), which enables us to represent the complex spectral morphology in a two-dimensional projection map while still preserving the properties of the local neighbourhoods of spectra. We find that the majority (178,483) of the 209,533 Galah spectra considered in this study represents normal single stars, whereas 31,050 peculiar and problematic spectra with very diverse spectral features pertaining to 28,579 stars are distributed into 10 classification categories: Hot stars, Cool metal-poor giants, Molecular absorption bands, Binary stars, H$alpha$/H$beta$ emission, H$alpha$/H$beta$ emission superimposed on absorption, H$alpha$/H$beta$ P-Cygni, H$alpha$/H$beta$ inverted P-Cygni, Lithium absorption, and Problematic. Classified spectra with supplementary information are presented in the catalogue, indicating candidates for follow-up observations and population studies of the short-lived phases of stellar evolution.
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