mayaradaher/challenge-Amazon
The app uses the Gemini language model to generate personalized book recommendations.
Handles 300+ MB Amazon purchase datasets optimized through Parquet conversion and extensive data cleaning for fast interactive analysis. Built with Plotly Dash, it provides three analytical views: purchase trends (2018-2022), customer demographics, and AI-driven book recommendations. The Gemini LLM integration analyzes individual user profiles and purchase histories to generate personalized suggestions, deployed on Google Cloud Platform.
Stars
30
Forks
6
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 24, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/mayaradaher/challenge-Amazon"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
ShowayLiao/OtakuNeko
🐱 你的二次元赛博哈基米 | 基于 LLM 的智能化番剧管理与分析助手。支持 Bangumi 数据同步、AI 深度画像分析、年度总结海报生成与个性化推荐。
VectorInstitute/health-rec
MVP of a recommendation system for health and community services
amine-akrout/llm-based-recommender
AI-powered fashion recommendation system leveraging LLMs, embeddings, and retrieval techniques...
EdIzaguirre/Rosebud
Let's discover films.
polarbear333/rag-llm-based-recommender
Explore a smarter way to shop online with this full-stack project built on the infrastructure of...