Project Purpose
Develop a web application (FoodHub) that recommends personalized recipes to users based on their dietary preferences, allergies, and cooking expertise.
Goals
- Create a user-friendly interface for inputting dietary preferences and receiving recipe recommendations.
- Integrate web scraping techniques to gather recipe data from various online sources.
- Implement machine learning algorithms to analyze user data and recommend recipes with high accuracy.
Challenges
- Data cleaning and normalization: Ensuring consistency and usability of scraped recipe data.
- Dealing with recipe variations: Accounting for different cooking styles, ingredients, and portion sizes.
- User feedback integration: Continuously improving recipe recommendations based on user preferences and engagement.
Achievements
- Developed a user-friendly web application with an intuitive interface for recipe recommendations.
- Successfully integrated web scraping to access and utilize a vast database of recipes.
- Implemented machine learning algorithms to generate personalized recipe suggestions based on user profiles.
