Recommender Systems with Machine Learning - Exploring Genres

The video tutorial explores a dataset focusing on genres. It begins with an introduction to the dataset and checks for missing genre information. The tutorial demonstrates how to handle missing data and clean the dataset by replacing slashes in genre entries with spaces. The video concludes with a preview of counting genre occurrences in the next session.

What is the first step taken to handle missing genre information in the data set?

• Replace missing genres with 'Unknown'

• Check for entries with no genre listed

• Add a default genre to all entries

• Ignore the missing genres

What does the code print when there are no missing genres in the data set?

• An error message

• Zero missing genres

• A list of all genres

• The number of missing genres

What action is suggested for data sets with many missing genres?

• Highlight them in the data set

• Drop the entries with missing genres

• Replace them with 'Unknown'

• Leave them as they are

What is the purpose of resetting the index after handling missing genres?

• To remove duplicates

• To ensure continuity in the data set

• To sort the data set

• To add new entries

What issue is identified with the genres column that needs correction?

• Genres are missing

• Genres are in uppercase

• Genres are duplicated

• Genres contain slashes

What is the solution proposed for the issue with slashes in the genres?

• Convert slashes to commas

• Remove the slashes

• Ignore the slashes

• Replace slashes with spaces

What is the next step after replacing slashes in the genres?

• Count the number of occurrences for each genre

• Add new genres to the data set

• Sort the genres alphabetically

• Remove duplicate genres