Predictive Modeling and Sentiment-Driven Recommendation System for Enhancing Customer Satisfaction in E-commerce
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Updated
Nov 1, 2024 - Jupyter Notebook
Predictive Modeling and Sentiment-Driven Recommendation System for Enhancing Customer Satisfaction in E-commerce
Product-Reommendation-System
This is a paper I worked on during "Scientific Paper 2"-class as a preparation for my upcoming thesis. The paper was graded with 1.7
Welcome to the Product Recommendation System repository! This project aims to build a recommendation system based on a dataset from Kaggle to provide personalized product recommendations to users.
This is a Kaggle competition, H&M Group invites to develop product recommendations based on data from previous transactions, as well as from customer and product meta data. The available meta data spans from simple data, such as garment type and customer age, to text data from product descriptions, to image data from garment images.
Add a description, image, and links to the productrecommedation topic page so that developers can more easily learn about it.
To associate your repository with the productrecommedation topic, visit your repo's landing page and select "manage topics."