How does Adam Optimizer work?

Adam maintains per-parameter running averages of both the first moment (gradient mean) and the second moment (gradient variance), using these to dynamically adjust each parameter's effective learning rate. The algorithm combines the benefits of momentum (smoothing gradient updates over time) and RMSProp (per-parameter learning rate scaling), producing fast and stable convergence across diverse model architectures and tasks. The platform strengthens ent