We constructed an ML model using the database built through DFT simulations, to predict atomic-level ground-state PDOS of a Si atom, including both valence and conduction bands, from the input Si-K ELNES/XANES. Given the difficulty in determining the absolute intensity of ELNES/XANES spectra in actual experiments, we normalized each input Si-K ELNES/XANES spectrum to have a maximum intensity of 1.0. The ML model is based on a one-dimensional convolutional neural network, designed to directly predict the ground-state PDOS about s-and porbitals separately from the output layer using the Si-K ELNES/XANES as input. The detailed model architecture is described in Supplementary Material C. The data was split into training, validation, test sets with a ratio of 6:2:2.