Task is to design a personalized recommendation system for music. Depending on experience level of the students, they can choose it to be content based or popularity based model. Content based model will require processing music features and recommending similar music. Extra points will be awarded if students can deploy the recommendation system through a web application or mobile application.

Skills Required: Python, Object-Oriented Programming, Knowledge of Recommendation Systems, Matrix Factorization, Collaborative Filtering. Famous DL Libraries like Tensorflow or Keras. Optional Skills include Full stack web app, Android/iOS App Development.

1. Understanding basics of Recommendation Engines
2. Overview video by Siraj Raval
3. Python Implementation of Popularity Based & CF Method
4. Hulu Blog Post on Applying Deep Learning to Collaborative Filtering
5. Quora Answer on Spotify Methods of Recommendation System
6. Collaborative Filtering in Spotify - Requires Mathematics Understanding.
7. Another Python Implementation
8. Thesis of Project on Music Recommender
9. Research Paper on Future Perspectives

• Nikhil Pandey
• Ronak Sakhuja
• Rajat