• Indu J
• Naveen Kumar G

The most important part of data analysis is to understand it in a better manner. Here, the analysis of product reviews on amazon is done since the reviews are unstructured or otherwise, they are unorganized. This analysis of unstructured data can be made simple by sentiment analysis that automatically tags the data and process large amount of data in an efficient manner.The proposed method used an ensemble approach of naïve bayes, the K-Nearest Neighbours (KNN) and Long Short Term memory (LSTM) and National Language Tool Kit (NLTK). The customer review dataset is trained and grouped using LSTM approach & KNN respectively. Further, the classification is done using Naïve Based model. The proposed predicted model leads to a perfect sentiment analysis of classifying Amazon reviews as positive, negative, and neutral.

KNN, NLTK, LSTM, Sentimental Analysis.

"Amazon Product Reviews Sentiment Analysis using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.d234-d239, September-2022, Available :http://www.jetir.org/papers/JETIR2209329.pdf

"Amazon Product Reviews Sentiment Analysis using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppd234-d239, September-2022, Available at : http://www.jetir.org/papers/JETIR2209329.pdf