Open Radio Access Network (O-RAN) has recently emerged as a new trend for mobile network architecture. It is based on four founding principles: disaggregation, intelligence, virtualization, and open interfaces. In particular, RAN disaggregation involves dividing base station virtualized networking functions (VNFs) into three distinct components - the Open-Central Unit (O-CU), the Open-Distributed Unit (O-DU), and the Open-Radio Unit (O-RU) - enabling each component to be implemented independently. Such disaggregation aims to improve system performance and allow rapid and open innovation in many components while ensuring multi-vendor operability. As the disaggregation of network architecture becomes a key enabler of O-RAN, the deployment scenarios of VNFs over O-RAN clouds become critical. In this context, we propose an optimal and dynamic placement scheme of the O-CU and O-DU functionalities either on the edge or in regional O-clouds. The objective is to maximize users' admittance ratio by considering mid-haul delay and server capacity requirements. We develop an Integer Linear Programming (ILP) model for VNF placement in O-RAN architecture. Additionally, we introduce a Recurrent Neural Network (RNN) heuristic model that can effectively replicate the behavior of the ILP model. We get promising results in terms of improving users' admittance ratio by up to 10% when compared to baselines from state-of-the-art. Moreover, our proposed model minimizes the deployment costs and increases the overall throughput.