Predicting Water Quality using Machine Learning Techniques

Water quality is a basic factor for the supportability of environments, human health and mechanical forms. Poor water quality poses several health hazards and can have a significant negative influence on human survival. Assessing the water’s condition is an essential stage in managing the sources of fresh water. The World Health Organization’s annual report shows that a shortage of clean drinking water is killing or injuring a large number of people. Preserving the ecological balance and securing water resources are crucial in light of the growing concerns over the environment around the world. The main objective of this research work is to measure water quality through Machine Learning (ML) techniques. This research study examines supervised regression algorithms like Decision Tree, Support Vector Machine, Random Forest and K-Nearest Neighbors.