The project helps us predict which cosmetics are good for us from a large dataset of cosmetics.
Preprocessing the ingredient lists is done via word embedding, then visualizes ingredient similarity using the Dimensionality-Reduction technique called t-SNE, and the visualization is done using Bokeh.
It is a content-based recommendation system based on the chemical components of cosmetics.
This Project also includes the concepts of natural language processing and word embedding.