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This machine learning project aims to leverage a comprehensive dataset of podcast engagement metrics to develop predictive models and derive insightful audience trends. By applying advanced analytical techniques, the project will explore listener behavior, demographic patterns, and episode-specific features to predict future listenership trends.

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therapist3003/PodLytics

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PodLytics

This machine learning project aims to leverage a comprehensive dataset of podcast engagement metrics to develop predictive models and derive insightful podcast trends. By applying advanced analytical techniques, the project will explore demographic patterns, and episode-specific features to predict future episode performance trends.

For more - Checkout ideas.txt

Datasets used:

  1. shows.csv : https://drive.google.com/file/d/18dj7zxr-E71WcqrhuDb-eoDC5-66oFAG/view?usp=sharing
  2. metadata.tsv : https://drive.google.com/file/d/1J_LSTzT9MiSH344mKTrbVIZiAJsU0G4S/view?usp=sharing (Obtained from Spotify Official)

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This machine learning project aims to leverage a comprehensive dataset of podcast engagement metrics to develop predictive models and derive insightful audience trends. By applying advanced analytical techniques, the project will explore listener behavior, demographic patterns, and episode-specific features to predict future listenership trends.

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