The 1st place solution for SIGIR 2020 E-Commerce Workshop Multimodal Product Classification Challenge
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Updated
Aug 3, 2020 - Jupyter Notebook
The 1st place solution for SIGIR 2020 E-Commerce Workshop Multimodal Product Classification Challenge
SAP Commerce extension using TypeSafe's Jev to moderate product reviews and suggest product categories and classification attribute values: dry runs on your own data first, an audit record per decision. Plus a Claude Code skill.
Implementation of ML algorithms for FlipKart Product Category Classification based on the product's description and other features.
Build a fastText product classification model that can predict a normalized category name for a product, given an unstructured textual representation.
Machine Learning - Multiclass Classification
Categorize and classify anything into a taxonomy or categories using an API that utilizes ChatGPT. Use cases: Classify products into a taxonomy. Classify texts/paragraphs based on predefined categories. Resolve complex taxonomy problems.
API MLOps de classification multimodale Rakuten combinant texte et image avec FastAPI, Docker, DVC, PyTorch et tests automatisés.
End-to-end MLOps pipeline for multimodal e-commerce product classification (text + image) — ingestion, training, inference and monitoring.
PyTorch multimodal classification pipeline combining ResNet-18 vision backbone with nn.EmbeddingBag text embeddings to categorize products from images and titles.
Source Code for User Bias Removal in Fine Grained Sentiment Analysis (CODS-COMAD 2018, DAB@CIKM 2017)
Classify e-commerce product descriptions into categories (Household, Books, Electronics, Clothing & Accessories) using SVM and Random Forest models with TF-IDF and Word2Vec representations. Includes data preprocessing, hyperparameter tuning, and model evaluation for performance comparison.
The KTRU code is issued only when the catalog rules leave exactly one position; otherwise the supplier gets a question, not a guess. Product card builder for Russian public procurement: fills characteristics from a free text description on local models, no paid API
Identification of fashion products using deep learning
NCM (Nomenclatura Comum do Mercosul) codes, their descriptions and hierarchy in formats easy to parse.
CentraleSupélec/OpenClassrooms Data Scientist 2024-2025 - Projet 6
Classification de produits avec leurs images et leurs descriptions.
[FRANCAIS]Étude comparative de 10 méthodes d'extraction de features pour e-commerce de luxe | [ENGLISH] Comparative study of 10 feature extraction methods (vision + NLP) for luxury e-commerce classification
Deep Learning for product classification with NLP
A clean, modular, and ML-powered pipeline for grouping and classifying electronic product listings (Laptops & TVs) from noisy vendor specifications using SBERT embeddings, threshold tuning, and confidence scoring. Includes advanced insights, bundle detection, and optional bonus challenges.
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