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  3. Feature Engineering for Machine Learning in Python

Exercise

Finding the most common words

Its always advisable once you have created your features to inspect them to ensure that they are as you would expect. This will allow you to catch errors early, and perhaps influence what further feature engineering you will need to do.

The vectorizer (cv) you fit in the last exercise and the sparse array consisting of word counts (cv_trigram) is available in your workspace.

Instructions

100 XP
  • Create a DataFrame of the features (word counts).
  • Add the counts of word occurrences and print the top 5 most occurring words.