This is the Case Study for Predicting with Probability. In it, you will use Spotify data and probability distributions to recommend songs listeners will love and spot the next song to hit the Top 100.
Spotify's Top 100
Matching a Single Feature
Matching Multiple Features
Recommender First Steps
Using Conditional Probability
Using the Law of Total Probability
Use Spotify data and probability distributions to build a recommendation engine filled with songs listeners will love. Then use this data to pinpoint which features will help an artist break into the Top 100.
- Probability as counting
- Probability Mass Functions (PMF)
- Cumulative Distribution Functions (CDF)
- Conditional Probability
- Joint Probability
- The Law of Total Probability
- Bayes’ Theorem, Normalization
Prerequisites and next steps
Highly recommended to take after completing Predicting with Probability.