Ambeone Student’s Projects Gallery
Based on the Big Data Analytics & Machine Learning Techniques taught in Ambeone’s Programs
This is a Gallery of some glimpses Data Science projects done by recent Ambeone students as part of their program.In case you are interested to know more about a particular project/projects, you may contact us for details .
Using Data Science to Understand Music Trends over last 10 Years
Submitted by: Daniel Alex
Spotify over the decade!
Music Trend Analysis!
Overview
This Data Science project analysed the music trend over last decade based on spotify data
Objective
- What are the most important audio aspects of hit music
- Past, present and most likely future trends in music
- Is modern music changing?
Data Preparation
- Over 600 of the most streamed spotify songs from 2010-2019 were analyzed to analyze the trend using following attributes:Title
– Artist
– Top Genre
– Year
– bpm: Beats per minute
– nrgy: Energy
– dnce: Danceability
– dB: Loudness in terms of decibels
– live: Is the song played in studio or live?
– val: Valence – Musical positiveness conveyed by a track. High valence tracks are more positive and vice versa
– dur: Song Length
– acous: Not having electrical amplification
– spch: Speechiness
– pop: Popularity
Data Science Techniques and Models used
- Data Cleaning and Transformation
- Advanced Data Visualization
- Correlation and Linear Regression Model
Key Results
- Interesting Trends were noticed . As outlined in the below presentation.
