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E-commerce Product Recommendation System (Streamlit App)

Demo Video

Demo Thumbnail

Watch my video on Vimeo

Description

"I developed and deployed an interactive web application called 'Beauty Products' for personalized product recommendations in the e-commerce space. This system utilizes multiple recommendation techniques to suggest items tailored to individual user preferences, enhancing the customer shopping experience

Key Features

  • Multiple Recommendation Strategies:

    • Rating-based: Recommends products with high customer ratings, making it easy for users to discover top-rated items.
    • Content-based: Analyzes product attributes such as category, brand, and description to suggest items similar to those the user has viewed or purchased.
    • Collaborative Filtering: Recommends products based on the purchase history of users with similar preferences.
    • Hybrid Approach: Combines different recommendation techniques to provide the most relevant and personalized suggestions.

  • User-friendly Interface: Built using the Streamlit framework, the app features a simple, intuitive interface with a search bar and customizable recommendation settings. The interface displays recommended products, including images and relevant details.

  • Example: A user can search for a specific product (e.g., nail polish), and the system will recommend similar products based on customer reviews, ratings, and product features.