Fruit Classifier

About this project

Developed a machine learning CNN pipeline in Python to classify fruit images with high accuracy. The project involved data collection and cleaning, image preprocessing and augmentation, model architecture design, training and hyperparameter tuning, evaluation with confusion matrices, and deployment of the final model. Preprocessing steps included resizing, normalization, and augmentation techniques such as rotation, flipping, and color jittering to improve generalization.