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Exercise

Comparing BoW and TF-IDF representations

You're part of the analytics team at a wearable tech company. Your goal is to help product managers understand customer feedback on the company's new smartwatch. You've already preprocessed the text and created two representations: bow_matrix using CountVectorizer(), and tfidf_matrix using TfidfVectorizer(). In this exercise, you'll visualize and compare the two to better understand how each captures word importance.

Instructions 1/2

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  • 1
    • Create a DataFrame using the provided bow_matrix, and plot a heatmap to visualize word frequencies for each review.
  • 2
    • Create a DataFrame from the tfidf_matrix, and plot a heatmap to visualize the TF-IDF scores.