Epilepsy is the most common chronic neurological disorder. Clinical neurologists use Electroencephalography (EEG) to record the voltage fluctuations within the brain via surface scalp electrodes. The EEG recording of an epileptic patient may show interictal epileptiform discharges (IEDs), which are intermittent electrophysiological events occurring between 2 seizures. Visual analysis of the EEG recording for IED is a time-consuming process that might take a neurologist up to 4 hours. This research leverages clinical data from patients with epilepsy collected at the Alfred Health and Royal Melbourne over the past 10 years and investigated different deep learning architectures to automate this process.