♦️ INTRODUCTION

🌟 Motivation

Today consumers are more health-conscious about their food choices than ever. They check the health claims on the front packaging as well as the product's ingredients to make sure the product is safe and contains as least unnecessary chemicals or additives as possible.

However, manufacturers often use misleading labels to deceive customers into buying their products such as "natural", "no added sugar", "low-calorie". When buying a food product, many questions may arise such as: "What do these nutrition facts on the label mean?", "How do I know if this product is actually safe and healthy?"

With enthusiasm in health and ingredients analysis, I want to build a user-friendly web application that could help any person understand about the products they choose and raise awareness about the importance of nutrients and food choices to our health

🌟 Proposal

  1. Input:
  2. Output:
    1. Prediction & Classification of food product
      • Predict Nutrition score
      • Classify Processing level of food
    2. Additives Detection
      • Extract ingredients on product's label to identify additives
    3. Recommendation based on similar nutrients
      • Recommend similar products to user's preferences

🌟 Summary

Main Goals*:*

♦️PROJECT DESCRIPTION

🌟 Dataset


🌟 Techniques