The Amazon Food Review Analysis project is a machine learning-based solution to classify product reviews into two categories: positive or negative sentiment. Leveraged NLP techniques to preprocess the textual data and extract meaningful features.Utilized the NLTK library for text preprocessing tasks. Employed various ML algorithms including Naive Bayes, Random Forest, and Decision Tree for classification.The project achieved an accuracy of 98% in classifying Amazon food reviews into positive or negative sentiment. Amazon data set is availbale on Kaggle : https://www.kaggle.com/code/dhananjaybiyani/amazon-food-review-analysis/input
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The Amazon Food Review Analysis project is a machine learning-based solution to classify product reviews into two categories: positive or negative sentiment.
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