In this chapter, we delve into the diverse applications of Machine Learning (ML) techniques within earthquake monitoring systems. Our exploration encompasses essential tasks in seismology, such as earthquake detection and picking, earthquake localization, magnitude estimation, seismic phase association, source discrimination, earthquake early warning systems, intensity prediction, and landslide analysis. The ML techniques exhibit the capability to serve as an automated earthquake monitoring system by accurately picking the P-wave arrival times and estimating earthquake magnitude and location. To validate this approach, we apply the automated ML system to the Egyptian seismic data recorded in the Red Sea region, revealing promising results for the future of automated earthquake monitoring systems driven by machine learning.