Aqua Foresight Logistics Regression Based Rainfall Prediction

The goal of meteorological science is to better comprehend Earth's atmosphere and create reliable weather prediction models. For weather forecasting, several techniques have been employed. In place of old-fashioned methods, machine learning techniques for weather prediction are rising in popularity recently due to their apparent accuracy. Rainfall rate is one of the key components of the weather system that directly affects the biological and agricultural sectors. Weather variations can create natural disasters at any time and have a catastrophic impact on the ecosystem. To forecast these variations and anticipate the weather changes ahead of time, a variety of ML techniques and algorithms can be applied. Previous research has noted that a variety of alternate approaches exist for weather prediction. Humidity, Fahrenheit, Direction of the wind, Moisture loss and other factors are taken into factoring. It is speculative to predict how much precipitation will fall overall throughout the summer and wet seasons. Logistic Regression methodology in Machine Learning can be helpful for assessing rainfall.