food_vision_big

• Developed the Food Vision Big model using TensorFlow, surpassing the performance of the 2016 DeepFood CNN model with an accuracy of 80.2% on the Food101 dataset comprising 101,000 images.
• Implemented advanced training techniques including prefetching and mixed precision training, reducing model training time to approximately 20 minutes compared to the 2-3 days reported in the DeepFood paper.
• Utilised TensorFlow Datasets for efficient data handling, created preprocessing functions, and optimised data batching, alongside deploying feature extraction and fine-tuning transfer learning strategies to enhance model training efficiency and accuracy.