In this tutorial, we perform a supervised multi-class classification task using triggers from matched filtering. Our neural network, built with Keras, distinguishes intermediate-mass binary black hole gravitational wave signals from various types of glitches. Through model training and evaluation, we explore how deep learning can separate astrophysical signals from instrumental noise in gravitational wave data.