Fashion-Recommender-System

Skills/Tools Used:

1. Python Programming Lnaguage
2. Deep Learning - ResNet50

Problem Statement :

Fashion enthusiasts often seek inspiration from websites like Pinterest to discover unique and trendy styles, with a desire to find similar clothing items for purchase.

Objective :

Robust recommender system that suggests closely matched clothing items based on user inputs, simplifying fashion exploration and discovery.

Outcome :

1. Personalization: The recommendations is personalized to each user's preferences, taking into account their individual style, size, and other relevant factors.
2. Enhanced User Experience: Simplifies the process of finding and discovering fashion inspirations, making it easier for users to explore and purchase similar items.
3. Increased Engagement: Drives user interaction and exploration of fashion options, fostering higher engagement with the platform.
4. Improved Conversion Rates: Relevant and appealing recommendations enhance user preferences, leading to higher conversion rates and increased purchases.
5. Continuous Improvement: Adaptable system that learns from user feedback and incorporates new trends for accurate and up-to-date recommendations.