Owing to exclusive thermal prospective of nanoparticles, diverse applications of such materials have been reported in heat transfer systems. The carbon nanotube (CNTs) is the modified class of nanoparticles which is preserve more stable thermal properties. The decomposition of CNTs with base materials offer special applications in enhancing thermal efficiency of energy systems, nuclear processes, sensors, diagnostic imaging etc. Following to such motivations in mind, the objective of current work is to present artificial neural network analysis for heat transfer problem due to suspension of carbon nanotubes-based nanofluid. Both single-walled and multi-walled carbon nanotubes are utilized to analyse the thermal impact of water base fluid. The source of flow is coaxially stretchable disks. The applications of porous medium phenomenon are reported to inspect the inertial effects. The problem is further updated by utilizing the radiative phenomenon, external heat generation and dissipation and slip constraints. The transport system is expressed via coupled nonlinear equations which are tackled via numerical computations.