This is Content based music recommendation system. I have used both audio features and lyrics (text based) features for recommending most similar songs to a given query song.

This web app recommends trending movies and songs by analyzing real-time tweets using sentiment analysis. It fetches data from Spotify and TMDB, and sends personalized email updates to users.

Chorus automatically suggests songs based on the music tastes of the guests, allowing them to vote on the next songs.

Hit Song Prediction Model - Master Thesis in Music and Acoustic Engineering - Politecnico di Milano

Your Pitch, an app that generates a curated daily Spotify song and calendar

Moodys is a song recommendation app which detects the mood of people and suggests appropriate songs. This app can be used to brighten up one's mood on a rainy weekend, create the atmosphere for a perfect date, and play melodious music for the young and the old alike.

In this system, we provide an overview of how music can affect the user's mood and how to choose the right music tracks to improve the user's moods.

In this project, I harnessed the Spotify API to gather rich song features, which I meticulously analyzed and leveraged to craft a content-based recommendation website. The user-friendly interface, powered by Streamlit

Module 04 Project for Flatiron School - Recommendation Systems

Implementation of a Song Recommendation system

How do platforms like Spotify seem to know exactly what song you want to hear next? Can we classify songs into genres based only on how they sound?

Get Data from the lyricis genius website through their API and create a hypothetical recommendation in this case for Harry styles's songs

"Stay updated with the hottest English songs of February 2025! Discover week-by-week trending hits, chart-toppers, and viral sensations. From pop to hip-hop, explore the latest music trends, streaming stats, and must-listen tracks. Keep up with the Billboard Hot 100 and global music rankings only at English Song Lyrics!"

A web application for song recomendation based on your current emotion

song recommendation system, recommend users songs with similar features, using ML technique.

MCalm detects people’s mood by using their facial expressions as well as by asking a few questions on a scale of 5, which would help people get a wider picture of their mood. Next comes the task to enlighten their mood by playing games , listening to jokes by bot and at last listening to soothing music.

A simple song recommendation model using gensim's Word2vec.

Created song recommendation android app.

Data visualization, hypothesis testing and song recommendation with Python