Recipe recommendation application based on the produce you have.
Presentation Report
Focus: Image Classification (w/ CNN), Text Classification (w/ NLP), Web Scraping, Data Engineering, and Design-to-Product Pipeline
Problem Statement:
- What dish can I cook tonight, using the produce I have in my refrigerator?
I spend a lot of time looking for recipes that would match the ingredients I have in my refrigerator. Sometimes ~30 minutes is spent on google searching, to get the one that's reasonable based on ingredients, prep time, nutritonal values, etc. I often feel that most cooking sites and mobile apps have too many functionalities to navigate through. So, I thought, "Wouldn't it be nice to have a personalized recipe-finder that simply takes ingredient photos as the input ?" I wanted to take a stab at this problem, i.e., building a recipe-finder that's personalized to my preferences.
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Tasks:
- Collect recipes (text data) by webscraping Epicurious. Scraped info includes recipe title, -ingredients, -instructions, nutritional values, and photos
- Collect images using Google API, for training a CNN model
- Build a neural network-based image classifier of produce
- Perform topic modeling analysis for recipe-tagging, i.e., grouping them into different dish categories
- Build a Flask app and a script that loads images from mail inbox to a folder on server for model prediction
