I developed a multiclass image classifier using a custom CNN (6.3M parameters) to categorize images across eight distinct classes. Built with TensorFlow and Keras, the model utilizes a 6-block architecture with dropout and early stopping to optimize performance on grayscale data. To make the model accessible, I integrated it into a Streamlit web app, allowing users to upload images and receive real-time classification results.