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Nutri-O-Matic

Project Overview

This project aims to develop a smart nutrition tracker application that leverages machine learning, mobile development, and cloud computing. The app will allow users to:

  • Scan Food: Quickly analyze food items to obtain nutritional information.
  • Predict Weight Classification: Utilize machine learning to provide insights into potential weight trends.
  • Track Nutrition: Monitor daily intake and set personalized goals.

Technologies Used

  • Machine Learning: TensorFlow, standard preprocessing techniques
  • Mobile Development: Kotlin, CameraX, Retrofit
  • Cloud Computing: Go, Google App Engine, Google Cloud Storage, MySQL, Flask, Google Cloud Run

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