Cosmetic Recommendation Engine

A web crawler crawling all cosmetics information from Sephora implemented in Scrapy

监控丝芙兰是否补货的爬虫脚本

This web crawler gathers the latest details, variations, imagery and pricing informations of a catalog of products given their urls from their corresponding online stores and prepares files ready for upload to your e-commerce platfrom. It was built with the purposes of making product additions easier for e-commerce retailers.

Sephora is an online e-commerce website for personal care and beauty products. Signup and login functionality , User and admin dashboard , Product and cart page are some of the features. Built the backend via NodeJS and MongoDB. Created the admin dashboard with all functionality Designed product and single product page.

Identifying fake reviews on Sephora using One Class SVM

A recommender system for cosmetic products, implemented from scratch using Python.

Built upon an existing open-source project to analyze cosmetic product pricing by examining ingredients, brand influence, and customer ratings. Enhanced the project with ingredient scoring, brand analysis, and data visualizations using Python and Sephora data.

A hybrid recommendation system combining Item-Based Collaborative Filtering and Content-Based Filtering to suggest skincare products based on user preferences, product ingredients, and ratings. Features a Flask API and an interactive Streamlit Web App for personalized recommendations.

Identifying fake reviews on Sephora using MLP autoencoder with anomaly detection

Personalized recommender system for Sephora's cosmetics e-commerce platform. Using content-based filtering, with TF-IDF Vectorizer to extract product features and cosine similarity to recommend similar items based on user preferences. And collaborative filtering with SVD for identifying user patterns and recommending highly-rated products.

Chrome Extension Project

Sephora is one of the largest and most important international stores. Accordingly, I did a data analysis that shows me the most frequently asked questions on Sephora

Find an business insight from e-commerce sephora dataset

SQL + Python exploration of Sephora product data. Includes analysis of brands, categories, prices, ratings, and value-for-money metrics, with visual insights in Jupyter notebooks.

Excel dashboard analyzing Sephora skincare pricing, sentiment, and product mix.

Sephora reviews scraping spider

Sephora web scraped data, on sale on Databoutique.com. Dataset created with web scraping, full snapshot of the website.

Sephora reviews Q&A scraper

🕷️ Collect and analyze detailed product reviews from Sephora with this automated scraper, transforming scattered feedback into structured data for insights.