## 3.2 Case Study: Topping the Charts with Spotify

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

Boosting Performance

### Course description

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.

### Topics covered

- 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.

Up next

### 4.1 Building Regression Models

Leverage the power of correlation and regression to understand relationships and make predictions with data.

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