Predicting rainfall is one of the more difficult tasks because there are so many variables to take into account. A brand-new technique for predicting rainfall has been suggested. The suggested approach employed hyper-tuned settings using machine learning techniques based on regression. Three different machine learning algorithms, specifically regression models, trained the dataset. For the purpose of predicting rainfall, the proposed model included machine learning, Ridge regression, Logistic regression, and Lasso regression. Online data collection for experimental purposes spans the years 1901 to 2015. The experimental findings point to a respectable advancement over established techniques for rainfall forecasting. By achieving lower MAE error values, the proposed performed better than the compared models.

rainfall predictions, HyperTuning, Machine Learning, MAE,CNN.