Bill-Klay/Skincare-Recommendation-Android-Application

Skincare recommendation android application that uses dataset from Kaggle and scrapped data from cosmetics websites to work a Tf-IDF vectorizer for content based filtering, and KNN and Decision trees for collaborative based filtering. The notebook also contains other approaches for POC including SVD. Backend APIs are based on Flask, Android application is made using Java with Android Studio whereas Firebase acts as the database and the middleware for relaying login information as well to serve the data to the application.

Skincare-Recommendation

Backend > Flask backend minus the templates
Data > All the data prepared, processed and implemented
Images > Important figures for the project ERD, design etc.
Notebooks > All the POC and model implementations
Skincare > Java android application
Wireframes > Wireframes for the application design
flaskBackEnd > Visual Studio project for the flask backend
heroku main > flask project deployed to heroku

Rest of the documents in the main folder complete the documentation aspect of the project.