The studies article delves into the evolution of using deep learning models for difficult analyses of optical tomography (OCT) snapshots, especially for classifying macular diseases. Its primary goal is to set up foundational information of the capability to figure subtle alterations in retinal shape and age-associated macular degeneration (AMD) development. in addition, it endeavors to differentiate AMD into its exudative and non-exudative sorts, thereby broadening the study horizon. The deep mastering version utilized is professional at extracting complex functions from huge datasets, thereby no longer the handiest enhancing accuracy but additionally refining type. This novel studies street holds promise no longer only in advancing diagnostic capabilities but also in imparting a truthful and green way of becoming aware of AMD and its wonderful subtypes through a meticulous evaluation of OCT images.