The project using Model MobileNet V2 from tensorflow https://keras.io/api/applications/mobilenet/

Data: Dataset Columns: 15 different types of food

 ** class_labels = 
  
  ['cheesecake', 'chocolate_cake', 'chocolate_mousse', 'fish_and_chips', 'french_fries', 'fried_calamari', 
    'fried_rice', 'gyoza', 'hamburger', 'hot_dog', 'oysters', 'pho', 'pizza', 'sushi', 'tacos']**

Image Dimensions: Standardized to 224x224 pixels

Training sample size: 11250 images belonging to 15 classes. Validation sample size: 3750 images belonging to 15 classes.

Dataset from Food_101: https://www.kaggle.com/datasets/dansbecker/food-101

The project is designed for the Final Project of CSCI 184: Applied Machine Learning in Santa Clara University