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

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

E-Commerce web application based on Django framework.

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.