The 1st place solution for SIGIR 2020 E-Commerce Workshop Multimodal Product Classification Challenge

This repository contains code and data download instructions for the workshop paper "Improving Hierarchical Product Classification using Domain-specific Language Modelling" by Alexander Brinkmann and Christian Bizer.

Proper categorization of e-commerce products enhances the user experience and achieves better results with external search engines. The objective of the project is to classify a product into four given categories, based on its description available on an e-commerce platform.

This repository illustrates the task of applying Machine Translation ( Seq2Seq Attention Network ) for Product Categorization of an E-Commerce Website data (Flipkart), classification of the description of products into the primary category of their category tree, and documenting the path to an optimal model pipeline

E-Commerce web application based on Django framework

E-commerce Product Categorization Model Using Deep Learning

E-Commerce web application based on Django framework.

This ML model is trained on BestBuy dataset and predicts 10 categories of product on the basis of title and description.

This is an ecommerce website for Pardo by Mireia Pardo. STREAM4 project of #codeinstitute´s diploma in Fullstack-Software-Development // Pardo by Mireia ecommerce

Masterschool's capstone project integrating skills and tools for data analysis.