Textbook recommendation on Inverse Problem Theory

Question

I am looking for a textbook on inverse problem theory, which includes both Regularization and Bayesian approach for inverse problem solving, including data assimilation, preferably machine learning aspects of it included (but not strictly needed). I want the focus on applications and coding, with bare minimum focus on mathematical definitions and theorems. I am currently reading Nakamura and Potthast's Inverse Modeling (link is here) and my eyes are completely glossing over the ton of mathematical details present.