Bag_of_Words.py

Summary of What the Script Does:

1. It takes a dataset of text (movie reviews in this case) and processes it to remove HTML tags, non-alphabetic characters, and stopwords.
2. It transforms the cleaned text into numerical features using the Bag of Words model, where each word in the reviews is counted and represented as a feature.
3. It prints a sample of the top features (words) that were extracted from the reviews.

This is a typical text preprocessing pipeline used to prepare textual data for machine learning models.