The marine system is now very complicated as like for managing, transportation, costing, maintenance and environment safety actions as well. Ship type classification with radiated noise helps monitor the noise of shipping around the hydrophone deployment site. This project introduces a convolutional neural network to classify the ship types based on artificial intelligence techniques. First, different ship types are collected from open source Kaggle website at high-resolution images and split into training and testing datasets. Second, a ship classification model is constructed based on deep convolutional networks . Finally performance metrics are calculated in terms of accuracy, precision, recall, F1 score.