Supervised Machine Learning algorithm using Sentiment Analysis based on customer feedback for smart phone product

Nowadays, there are several e-commerce giants namely Amazon, Flipkart and e Bay which have been built on forefront with Machine Learning (ML) that certainly manages the world. This is particularly seen currently in the sector of e-commerce and provided its consequences. However, the ML application in general and in its advancement has produced deep impact in our life style. In the e-commerce field, the technique of ML is implemented and accomplished with better results. Therefore, the research of AI has attained an excellent level with sublevel of ML and deep learning application with a minimal method that is proceeding to concrete future business. Sentiment Analysis (SA) is a technique used for analyzing data that has expressed in terms of text and even for discovering sentimental and emotional content from the text. SA is a process of deep learning method which is an advancement of ML, utilized for finding information with positive, neutral and negative from the review of customers. The identification process and analysis of customer feedback is important using Natural Language Processing (NLP), is said to be sentiment analysis. In this research, the dataset has considered about smart phone products with 4000 customer's feedback and ratings for Prod_ID as input. It is utilized for the analysis based on related categories namely Prod_ID, Prod_name, Brd_name, Rating, Rvew and Rvew_vote. The performance evaluation of classifier can be measured in terms of the accuracy. Based on the results it is observed that Neural Network (NN) has produced better accuracy than other classification algorithm with 98%.