E-Commerce Product Recommendation System Using Machine Learning

E-Commerce Product Recommendation System Using Machine Learning

Darshan M1, Ashwini C2

1Darshan M, Student, Department of MCA, UBDTCE, Davangere.

2Ashwini C, Assistant Professor, Department of MCA, UBDTCE, Davangere.

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Abstract- The goal of the machine learning-powered e-commerce product recommendation system is to provide a complete, end-to-end web-based platform that improves online shopping by making insightful product recommendations. This system has features for administrators as well as users, and safe access requires login credentials. To extract information from product photos, the system's backend uses machine learning models, specifically convolutional neural networks (CNNs) for image analysis. The user's buying experience is enhanced by the use of sophisticated machine learning techniques, which guarantee relevant and accurate recommendations. To sum up, our study highlights how important machine learning-driven recommendation systems are for increasing consumer engagement and generating income for e-commerce platforms. Through constant innovation and improvement, we strive to provide businesses with state-of-the-art resources to enable them to provide individualized and significant purchasing experiences.

Key Words: User Experience, Product Recommendation, Neural Network (CNN’s)