Classifying Amazon Reviews with Python: From Raw Text to 88% Accuracy

Automated excerpt

In this project, I built a machine learning model that classifies Amazon product reviews as Positive or Negative using NLP techniques. This is really helpful for the model to identify words properly. words = [word for word in text. split() if word not in stop_words] Machine learning models need numbers, not words. TF-IDF weighs words by how unique they are to each review — common words like "the" get ignored, meaningful words like "terrible" get prioritised.

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