Cosmetic Recommendation Engine
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- Jupyter Notebook
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sephora
Here are 23 public repositories matching this topic...
A web crawler crawling all cosmetics information from Sephora implemented in Scrapy
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- Python
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.
wordpress-plugin catalog webscraper woocommerce scrapy e-commerce startups startup-template imagery startup-resources woocommerce-extension sephora kyliejenner startup-code find-products macys qarece-web-crawler pricing-informations ecommerce-retailers ecommerce-platfrom
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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.
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- JavaScript
Identifying fake reviews on Sephora using One Class SVM
nlp machine-learning svm dataset beautifulsoup sephora yelp-dataset oneclasssvm deceptive-reviews fake-reviews classification-svm
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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.
python data-science ai eda data-visualization statistical-analysis business-intelligence data-analysis sephora consumer-insights beauty-industry
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A recommender system for cosmetic products, implemented from scratch using Python.
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- Python
Sephora is a French multinational retailer of personal care and beauty products. Featuring nearly 340 brands,along with its own private label, Sephora Collection, Sephora offers beauty products including cosmetics, skincare and many more.
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- JavaScript
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.
nlp machine-learning ecommerce collaborative-filtering recommendation-system flask-api sephora skincare content-based-filtering streamlit
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Identifying fake reviews on Sephora using MLP autoencoder with anomaly detection
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Dans le cadre de l'UE Visualisation des données massives en master 1 Informatique et Big Data
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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.
recommender-system cosine-similarity svd sephora singular-value-decomposition tf-idf-vectorizer product-recommendation
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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.
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Find an business insight from e-commerce sephora dataset
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Sephora reviews scraping spider
python json spider sentiment-analysis reviews sephora playwright product-review-scraper ecommerce-reviews sephora-reviews
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Excel dashboard analyzing Sephora skincare pricing, sentiment, and product mix.
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Sephora reviews Q&A scraper
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