Browsing by Author "1722351642"

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    Ecommerce Based Product Recommendation System
    (North-south University, 2021-11-30) Md. Mukith Al Alim; Md. Ashiqur Rahman Ovi; Md. Hasibul Hasan; Zeeshan Jamal; Dr. Shazzad Hosain; 1711376042; 1721444042; 1722351642; 1731699642
    This paper represents a noble approach to develop a Machine Learning method like Ecommerce Based Product Recommendation System for developing country like Bangladesh. The product recommendation system is a filtering system that seeks to predict and show the items that a user would like to purchase. Recommender systems have become increasingly popular in recent years and utilized in various areas, including movies, news, books, research articles, search queries, social tags, and products in general. It is an essential feature of the digital world. Because users are often overwhelmed by choice and need help finding what they are looking for. If a recommender system is set up and configured properly, it can be the reason for a significant boost in revenues, satisfied customers, and more sales. In this project, we have employed several machine learning algorithms (NCF, SVD, Encoder-Decoder, KNN) to build a recommender system for products and also have developed a website through which users can geta list of recommendations of products based on their preferences. These algorithms’ performancesare evaluated on different metrics. KNN has been selected to deploy on the website among all the algorithms.