To test the efficacy of our approach, we choose to model energetics of sub nanometer clusters of those elements which are traditionally described by the Sutton Chen (SC) type EAM potentials (Ag, Al, Au, Cu, Ir, Ni, Pb, Pd, Pt, Rh), and deploy the AL strategy to develop a NN potential model that can accurately predict the bulk as well as diverse geometries of nano clusters for those ten elements. For small cluster where bond-directionality effects are important, we show that popular spherically symmetric potential models such as embedded atom method (EAM) or its variants like Sutton-Chen (SC) and Gupta potentials, struggle to capture the diverse geometries and the dynamical properties. This is because of the presence of only a radially symmetric component in their functional form. Bond-order based empirical force field models (EFF) (e.g, Tersoff-type BOP, Reactive force field model ReaxFF ) account for bond directionality via an angular dependence. The existing parameterizations of these pre-defined models perform well for bulk structures, and close-packed (bulk-like) cluster configurations (at large sizes). For instance, the SC Potential works really well in predicting the bulk elastic properties of the ten FCC metals it describes. But they tend to fail when it comes to describing the potential energy surface for smaller sized clusters [ Fig 1]. These ten FCC metals represent excellent model systems to test our developed framework. We show that our TL and AL-NN are able to adequately represent the bulk and cluster energy landscape by sampling minimal amount of reference data (∼ 500-700 total structures in reference dataset). The performance of these NN in capturing bulk and cluster properties is discussed in detail.