In this micro-project, learners will develop a custom image classification model capable of distinguishing between three flower types: roses, sunflowers, and tulips. The project uses MobileNetV3, a lightweight deep learning model well-suited for edge devices, and uses transfer learning to fine-tune the model using a small, curated dataset.
This project is ideal for learners interested in computer vision, image processing, and model training using pre-trained architectures. It demonstrates best practices for preparing datasets, handling class imbalance, and structuring data for training with TensorFlow and Keras.
