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 .

Ambeone Data Science Project

 

Using Data Science to Understand Music Trends over last 10 Years

Submitted by: Daniel Alex

 

Ambeone Data Science Project

 

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.
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