T.J. Wilder

T.J. Wilder, a machine learning engineer at Intrepio specializing in generative AI for healthcare, discusses the fascinating world of autoencoders. He explains how these neural networks compress data to improve performance through dimensionality reduction and synthetic data generation. Wilder dives into various types of autoencoders, like variational and sparse, and their applications in enhancing model efficiency and interpretability. He also highlights their significance in addressing healthcare data challenges by generating realistic synthetic data.