Over the decades, water pollution has been a real threat to the living species. The real-time monitoring of drinking water is nothing less than a challenging task. This paper aims to design and develop a low-cost system for the real-time monitoring of water quality using Internet of Things (IoT) and Machine Learning (ML). The physical and chemical parameters of the water such as temperature, level, moisture, humidity, and visibility are measured using respective sensors. ESP8266, the core controller is employed to process the measured values from the sensors. The data acquired from Sensors are sent to the Django server. Random Forest (RF) and K-Nearest Neighbours (KNN) algorithm are used in the analysis and prediction of water quality.