Garbage Classification using MobileNetV2

In this project, I built an image classification model using MobileNetV2 and the Garbage Classification dataset from Kaggle to automatically identify 12 types of waste such as plastic, paper, glass, metal, and organic trash. The goal of the video was to demonstrate how transfer learning can be applied to a real-world sustainability problem by training a lightweight deep learning model that can run efficiently while still achieving strong accuracy. The workflow shown includes dataset preparation, image preprocessing, model training, evaluation, and testing predictions, highlighting how AI can support smart recycling and automated waste sorting systems. Kaggle Code : https://www.kaggle.com/datasets/mostafaabla/garbage-classification