Kaluza-Klein reduction of 11-dimensional supergravity on manifolds yields a 4-dimensional effective field theory (EFT) with supersymmetry. manifolds are therefore the analog of Calabi-Yau (CY) threefolds in heterotic string theory. Since 2017 machine-learning techniques have been applied extensively to study CY manifolds but until 2024 no similar work had been carried out on manifolds. We first show how topological properties of these manifolds can be learnt using simple neural networks. We then discuss how one may try to learn Ricci-flat metrics with machine-learning.