The first objective is to create a machine learning pipeline that when provided with a photo of a rice or chips image as input, it should accurately classify whether the given image is rice or chips.
The second objective is to create a machine learning pipeline that when provided with a photo of a dish as input, can accurately determine whether the dish belongs to Indian cuisine.
- What's interesting about this problem is it addresses the challenge of classifying the dish as rice or chips based on visual features, which aims to contribute to the accurate identification
- The dataset is compelling due to its substantial size (3250 images) and diverse attributes including 'Diet,' 'Cuisine,' 'Dish_name,' 'Home_or_restaurant,' 'Ingredients,' 'Healthiness_rating,' and 'Likeness.' This richness makes the dataset versatile
- The goal is to develop an optimal machine learning model that can accurately distinguish whether a given image is rice or chips and also predict if it belongs to Indian Cuisine or not