A Novel Approach Towards Fashion Trend Analysis System Using Machine Learning

Fashion is one of the most important aspects of people's lives and is widely considered as a significant aspect of personal expression and identity. With the growing trend of ecommerce and online shopping, the development of fashion recommendation systems has become increasingly important. These systems aim to provide personalized fashion recommendations to customers based on their individual preferences, style, and previous purchasing history. This research work provides an overview of the current state of fashion recommendation systems, including the various algorithms and technologies used, as well as their potential benefits and limitations. This research paper proposes the development of a fashion recommendation system that utilizes machine learning algorithms to suggest outfits to users. The system will analyze user preferences and past purchases to generate personalized recommendations. The study aims to evaluate the effectiveness of the system by conducting a user study, comparing its performance to traditional online shopping experiences. The findings of the research suggest that the proposed recommendation system provides an efficient and effective way for users to discover new fashion items that match their personal style and preferences. The research also identifies potential areas for improvement and future research in the field of fashion recommendation systems.