Music Personalization and Recommendation System for Voice-based Virtual Assistants/Mobile Apps
Jul 2018 - May 2019 (11 months)
* Developed and designed a music personalization and recommendation system by implementing machine learning algorithms and techniques to analyze user preferences and recommend personalized music content.
* Developed a collaborative filtering based recommendation engine to suggest music based on user preferences and behavior patterns.
* Incorporated natural language processing techniques to understand user queries and generate accurate music recommendations.
* Technologies used: Python, NumPy, Jupyter Notebook, TensorFlow, Scikit-Learn, MySQL, Django, AWS, Spotify APIs, Pytorch.