A golf swing requires full-body coordination and much practice to perform the complex motion precisely and consistently. The force from the golfer's full-body movement on the club and the trajectory of the swing are the main determinants of swing quality. In this research, we introduce a unique motion analysis method to evaluate the quality of golf swing. The primary goal is to evaluate how close the user's swing is to a reference ideal swing. We use 17 skeleton points to evaluate the resemblance and report a score ranging from 0 to 10. This evaluation result can be used as real-time feedback to improve player performance. Using this real-time feedback system repeatedly, the player will be able to train their muscle memory to improve their swing consistency. We created our dataset from a professional golf instructor including good and bad swings. Our result demonstrates that such a machine learning-based approach is feasible and has great potential to be adopted as a low-cost but efficient tool to improve swing quality and consistency.