Music Recommendation Engine
A Data Engineering & Deep Learning Research Project
Exploring how large-scale audio data, metadata pipelines, and representation learning power modern music recommendation systems. From raw audio waveforms to similarity-driven recommendations.
Data Engineering
Scalable pipelines, metadata ingestion, and unified feature stores. Handling terabytes of structured and unstructured music data.
Machine Learning
Deep audio representation learning, spectral analysis, and vector similarity search for content-based recommendations.