Library / Artificial Intelligence

E-Commerce Product Recommendation : RAG Systems

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About this course

By the end of this project, you will be equipped to perform context-based searches using Retrieval-Augmented Generation (RAG) systems and the OpenAI API, as well as develop a personalized recommendation system. You’ve been hired by ShopVista, a leading e-commerce platform offering products ranging from electronics to home goods. Your goal is to improve the platform's product recommendation system by creating a context-driven search feature that delivers tailored suggestions based on users' search phrases. You'll work with a dataset of product titles, descriptions, and identifiers to build a recommendation system that enhances the shopping experience.

Learning Objectives:

  • Prepare vector data for a Retrieval-Augmented Generation (RAG) system using OpenAI's text embedding models.
  • Implement cosine similarity to identify and understand data relationships and patterns, improving recommendation systems.
  • Utilize OpenAI APIs to perform efficient and effective context-based searches.
  • Design and develop context-rich prompts for a user-friendly product recommendation system.

This project will provide you with a comprehensive understanding of AI-powered search and recommendation systems, enabling you to grasp how cutting-edge technologies such as Retrieval-Augmented Generation (RAG) and OpenAI’s models can be applied to solve real-world challenges. As you work through the project, you'll learn how to prepare and manage large datasets, leverage advanced text embedding techniques, and use AI to improve user interactions with e-commerce platforms.

By implementing context-based searches and personalized recommendation features, you'll enhance your technical capabilities in areas such as natural language processing, vector-based data retrieval, and algorithm development. Furthermore, the practical experience gained from building a recommendation system for a leading e-commerce platform like ShopVista will deepen your problem-

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