Dataset for Characterizing viral samples using machine learning for Raman and absorption spectroscopy

We demonstrated the application of machine learning methods, such as convolutional neural networks and random forests, to predict the concentration of viral samples through Raman and absorption Spectroscopy. Our study demonstrates that concatenating the Raman and absorption data increases the prediction accuracy compared to using either Raman or absorption spectrum alone. In this dataset, we've included the raw and processed data files associated with the manuscript.