Image Sentiment Analyser classifies the sentiment of images using deep learning techniques. The project uses TensorFlow and Keras to build a sequential deep learning model for sentiment classification.
This project aims to classify images based on their sentiment (e.g., happy, sad, neutral, angry) using a convolutional neural network (CNN). The model is trained on a labeled dataset of images and can be used to predict the sentiment of new images.