aaf431/FTIR_and_Machine_Learning: Machine Learning Enhanced Spectroscopic Analysis

Python code and data for the submission "Machine Learning Enhanced Spectroscopic Analysis: Towards Autonomous Chemical Mixture Characterization for Rapid Process Optimization" There are two sub-folders. The first one, "Synthetic Data", is composed of multiple folders, with names that describes the chemical system. Each folder has a python script that contains the code to generate synthetic data to train and test machine learning models, and additional .csv files with the FTIR spectra for the individual constituents of each mixtures. The second folder, "Experimental Data" is also composed of multiple folder, one for each chemical mixture studied. Each folder has a python script to generate the regression models and the collected FTIR spectra for different mixtures of known composition.