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How can the implementation of supervised machine learning enhance the efficiency of discovering apparel that suits individual style preferences?

Hello! My name is Shailja Tyagi, and my Polygence project focuses on developing a supervised machine learning-based fashion recommendation system. I chose to work on this project because I am passionate about the intersection of technology and fashion. Today, fashion recommendation systems have become increasingly vital in addressing the challenges of choice overload and enhancing the shopping experience for consumers. By working on this research topic, I aim to gain a deeper understanding of how advanced machine learning techniques can be harnessed to solve practical problems in the fashion industry. Additionally, I aspire to pursue a career in artificial intelligence and machine learning, and this project aligns perfectly with my interests and career goals. In the final outcome of my research, I aim to create a research paper and code an algorithm. I hope to publish this paper or find other suitable ways to share and present my findings.
Graduation Year
Student review
The aspects which met my expectations were the number of resources given to complete the project and the research paper feedback.
Project description

In recent years, recommendation algorithms that present content based on user past preferences have gained significant popularity on platforms like TikTok, Instagram, and YouTube. These algorithms effectively connect individuals with products they desire, providing value to both users and content creators. This project proposes to create a similar suggestion algorithm for apparel and fashion. This algorithm will utilize supervised machine learning over a large pre-existing dataset of apparel purchases to provide fashion suggestions based on explicitly stated individual preferences. Such an approach can address the challenges of choice overload faced by individuals seeking to curate their wardrobes. Moreover, it has the potential to facilitate retailers by connecting them with customers actively seeking fashion items that align with their unique tastes. In today's world, fashion recommendation systems have become increasingly vital, enhancing the shopping experience and fashion discovery process for consumers. This research paper explores various techniques for developing a fashion-based recommendation algorithm and emphasizes the significance of recommendation systems. It presents an implemented model and evaluates its performance in suggesting apparel based on individual preferences, demonstrating the effectiveness of the proposed approach in enhancing fashion recommendations.

How can the implementation of supervised machine learning enhance the efficiency of discovering apparel that suits individual style preferences?
Project outcome

Research Paper, ML algorithm code, Published in R.A.R.S

PhD Doctor of Philosophy candidate
Comp Sci, Quantitative, Engineering
Computer Vision, Robotics, Machine Learning
Mentor review

He was helpful in terms of the structure of the paper and guidance throughout the coding process.

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