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Recommend musical artists part II

Suppose you were a big fan of Bruce Springsteen - which other musical artists might you like? Use your NMF features from the previous exercise and the cosine similarity to find similar musical artists. A solution to the previous exercise has been run, so norm_features is an array containing the normalized NMF features as rows. The names of the musical artists are available as the list artist_names.

This exercise is part of the course

Unsupervised Learning in Python

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Exercise instructions

  • Import pandas as pd.
  • Create a DataFrame df from norm_features, using artist_names as an index.
  • Use the .loc[] accessor of df to select the row of 'Bruce Springsteen'. Assign the result to artist.
  • Apply the .dot() method of df to artist to calculate the dot product of every row with artist. Save the result as similarities.
  • Print the result of the .nlargest() method of similarities to display the artists most similar to 'Bruce Springsteen'.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import pandas
____

# Create a DataFrame: df
df = ____

# Select row of 'Bruce Springsteen': artist
artist = df.loc[____]

# Compute cosine similarities: similarities
similarities = ____

# Display those with highest cosine similarity
____
Edit and Run Code