This project analyzes beauty industry trends through data-driven insights into product popularity, brand performance, and customer preferences. It explores patterns in consumer behavior, helping businesses make informed decisions to refine marketing strategies, enhance product offerings, and improve customer engagement.

Sentiment analysis of The INKEY List skincare reviews from the Sephora dataset using BERT, zero-shot classification, and TF-IDF with logistic regression. This project classifies reviews into positive, negative, or neutral sentiments, offering insights into customer satisfaction.

Sample dataset of 1001 Sephora products, extracted via Bright Data API, featuring essential data points for pricing optimization, product personalization, and market analysis.

System rekomendacji kosmetyków oparty na KNN, sugerujący produkty na podstawie ocen użytkowników.

Sentiment analysis of The INKEY List skincare reviews from the Sephora dataset using BERT, zero-shot classification, and TF-IDF with logistic regression. This project classifies reviews into positive, negative, or neutral sentiments, offering insights into customer satisfaction.

Beispiel-Datensatz mit 1001 Sephora-Produkten, extrahiert über die Bright Data API, mit wesentlichen Datenpunkten für Preisoptimierung, Produktpersonalisierung und Marktanalyse.

Bright Data APIを介して抽出されたSephora製品1001件のサンプルデータセットであり、価格最適化、製品パーソナライゼーション、および市場分析のための重要なデータポイントを備えています。

Bright Data API를 통해 추출된 Sephora 제품 1001개로 구성된 샘플 データセット로, 가격 최적화, 제품 개인화, 시장 분석을 위한 필수 데이터 포인트를 포함합니다.