The intensity of tropical cyclones in terms of the maximum sustained surface wind speed is predicted using machine learning and deep learning methods ,like support vector machine regressor , random forest regressor and long short term memory model (LSTM). The surface wind speed is predicted with some large scale environmental fetaures having a direct/indirect influence on the intenisficiation of tropical cyclone. First the features are extracted by averaging them over a radius of 500 km for each of the TC center and the data frame is prepared. Climatology plots and correlations are determined to understand their influence better. This process is done for both India meteorological department (IMD) and Joint typhoon warning center (JTWC) best track data . The dataframes are the converted to supervised learning and various models are deployed to predict the 6hr,12 hr,24 hr,48 hr,72 hr intensities.