Sentimental Analysis of Amazon Customers using Deep Learning Techniques

Online purchasing is becoming increasingly important in today's environment. The company concepts have been refashioned and utterly revolutionized and making it so simple for clients to buy what they desire with the press of a mouse click. 90% of shoppers try several online channels to judge the quality of their purchase. In this article, 568,454 fine food reviews of 74,258 goods and 256,059 consumers on Amazon were tracked over a ten-year period. To label our datasets, we employed both a manual and an active learning technique in our model. Various classifiers are utilized in the active learning process to provide accuracy until a desirable level is reached.