Project Analysis
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Spotify

About Project

Usage

The dataset can be used for:

  • Building a Recommendation System based on user input or preference.
  • Classification purposes based on audio features and available genres.
  • Any other application that you can think of. Feel free to discuss!

Column Description

  • track_id: The Spotify ID for the track.
  • artists: The names of the artists who performed the track. If there is more than one artist, they are separated by a semicolon (;).
  • album_name: The album name in which the track appears.
  • track_name: The name of the track.
  • popularity: A value between 0 and 100 indicating the popularity of a track. It is calculated based on the number of plays and recency of plays.
  • duration_ms: The length of the track in milliseconds.
  • explicit: Whether the track has explicit lyrics (true = yes, false = no or unknown).
  • danceability: A measure (0.0 to 1.0) of how suitable a track is for dancing, based on musical elements like tempo and beat strength.
  • energy: A measure (0.0 to 1.0) of intensity and activity in a track. Higher values indicate fast, loud, and noisy tracks.
  • key: The musical key of the track, mapped to standard Pitch Class notation (e.g., 0 = C, 1 = C♯/D♭, 2 = D, etc.).
  • loudness: The overall loudness of a track in decibels (dB).
  • mode: Indicates the modality of a track (1 = Major, 0 = Minor).
  • speechiness: Detects the presence of spoken words in a track. Values above 0.66 indicate mostly speech-based tracks.
  • acousticness: A confidence measure (0.0 to 1.0) of whether the track is acoustic. Higher values indicate acoustic tracks.
  • instrumentalness: Predicts whether a track contains no vocals. Values closer to 1.0 indicate instrumental tracks.
  • liveness: Measures the presence of an audience in the recording. Values above 0.8 suggest a live performance.
  • valence: A measure (0.0 to 1.0) of the musical positiveness of a track. Higher values indicate happier and more cheerful tracks.
  • tempo: The estimated tempo of a track in beats per minute (BPM).
  • time_signature: An estimated time signature, ranging from 3 to 7 (e.g., 3/4 to 7/4).
  • track_genre: The genre of the track.

Problem Statement

Objective

Proposed Solution

Technologies Used

Challenges Faced

Methodology

Result / Outcome

EDA
ML MODEL