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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.