A comprehensive guide to building a machine learning model for detecting radioactive isotopes using gamma spectroscopy data. The tutorial covers data collection from scintillation detectors, preprocessing techniques including normalization and noise augmentation, feature extraction from gamma spectra, and training an XGBoost
Table of contents
Methodology1. Gamma Spectrum2. Collecting the Data3. Training the Model4. TestingConclusionSort: