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It's Technocolabs Software Data Scientist Internship Project (1st Dec 2021 - 15th Jan 2022). In this project the team was instructed to analysis big data of Spotify users and to perform Statistical and Exploratory Data Analysis and Model Development for Predicting Listener Behavior.

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Spotify-Skip-Action-Prediction

Music providers are also incentivized to recommend songs that their users like in order to increase user experience and time spent on the platform. Machine learning in the context of music often uses recommender system. There hasn’t been much research on how a user’s interaction with music over time can help recommend music to the user.

🚀 About Me

Hola, mi nombre es Mudit I'm a Machine Learning and Data Science Enthusiast. I am interested in Business Analytics and Market Research as well as Predictve Finance Analysis. I am skilled in Python Language, SQL, C++, Data Science and ML , Data Visualisation and Keras/ Tensorflow, Stramlit and Analytics. Do checkout my repo!! Gracias :)

PROCESS OF PROJECT

  • EDA: Feature and Target Feature Relation & Feature Engineering
  • MODEL DEVELOPMENT
  • DEPLOYMENT OF ML MODEL

🔗 Links for Respective Project Works

Track Feature Dataset

Session Dataset

EDA : Track Feature

EDA : Log Session

EDA : Track and Session Merged

Model Development

Deployment :: codes and files

Project Report

Bankruptcy Predictor App

WEB APPLICATION

Spotify Skip Predictor App on deployed on Heroku

Web App 1

Web App 2

Web App 3

EDA Analysis and Feature Engineering Summary

Analysis 1

Analysis 2

Analysis 3

Analysis 4

Analysis 5

Feature Engineering 1

Feature Engineering 2

About

It's Technocolabs Software Data Scientist Internship Project (1st Dec 2021 - 15th Jan 2022). In this project the team was instructed to analysis big data of Spotify users and to perform Statistical and Exploratory Data Analysis and Model Development for Predicting Listener Behavior.

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