R&D

AI Recommender

Building a Smarter Music Recommendation Engine

To create an AI-powered music recommendation system by feeding a user's Spotify data into the Gemini API for deep preference modeling.

Timeline

2-3 months

Team

2-3 developers

Budget

$50,000

Results

1

AR

The Challenge

While standard recommendation algorithms are good, this project explored if modern LLMs could create more nuanced, personalized recommendations by understanding the deeper context of a user's listening history.

Our Solution

To create an AI-powered music recommendation system by feeding a user's Spotify data into the Gemini API for deep preference modeling.

Technologies Used

Scikit-learnSpotify APIGemini APIPython

Key Results

Demonstrated our ability to apply large language models (LLMs) to structured data to create sophisticated, personalized user experiences.

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