Recommendation System with Exploratory Data Analytics using Machine Learning
Manu Panwar, Amit Wadhwa, Sanjeev Kumar Pippal · 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) · 2021
Digital data is generated on a vast scale nowadays and has been for the past two decades. This phenomenon implies shift in how data is managed, and conclusions drawn from it. Furthermore, artificial intelligence approaches and procedures for new ideas of analyzing Big Data, Sentiment Analysis (SA), also known as Opinion Mining (OM), has been a hot topic in recent, because of its ability to extract value from data, it has been around for a long time. It is, however, a topic that has gotten more attention in the fields of engineering and linguistics. As a result, the goal of this research is to provide insights into the field of exploratory data analysis, as well as an orientation toward the study of a recommendation system employing big data in the context of an e-commerce system, through the use of machine learning. probable machine learning based model. Initially the research contribution briefly summarizes discussion of the strategies and processes currently used in Sentiment Analysis and further we work upon the analysis of a recommendation system with e- commerce data using LSTM Model.