Product Classification
ecommerce-product-classification-by-categories
🛍️ E-Commerce Product Classification Dataset
Dataset Description
This dataset contains 31,851 realistic English product descriptions across 33 e-commerce categories, designed for training product classification models.
Key Features
✅ 31,851 samples with natural language variations
✅ 33 product categories covering major e-commerce segments
✅ 4 seller personas: Professional, Individual, Reseller, Minimal
✅ Realistic noise: Typos, abbreviations, casual language… See the full description on the dataset page: https://huggingface.co/datasets/Lezh1n/ecommerce-product-classification-by-categories.Product_Image_Classification
Product Image Classification Dataset
Датасет изображений товаров, собранный с крупных узбекских маркетплейсов (asaxiy.uz, texnomart.uz, olcha.uz) для задачи автоматической классификации e-commerce продукции.
Описание датасета
Данный набор данных содержит фотографии товаров, разбитых по 5 основным категориям электроники. Данные прошли автоматическую очистку от поврежденных файлов и дедупликацию по MD5-хешу.
Категории (Classes):
headphones — Наушники… See the full description on the dataset page: https://huggingface.co/datasets/NurzatS/Product_Image_Classification.fsl-product-classification
Few-Shot Learning (FSL) Product Classification Dataset
Dataset Description
This dataset is designed for Few-Shot Learning (FSL) research in product classification tasks. It contains product images organized into 763 distinct classes, with an average of approximately 367 images per class (279,747 total images), making it ideal for training and evaluating few-shot learning algorithms in e-commerce and retail scenarios. Note that class numbers are not continuous.
Key… See the full description on the dataset page: https://huggingface.co/datasets/xixu-me/fsl-product-classification.Eyebrow-Makeup-Product-Image-Classification-Dataset
Eyebrow Makeup Product Image Classification Dataset
The current retail e-commerce industry faces the challenge of a wide variety of products and diverse customer needs, especially in the recognition and classification of eyebrow makeup products. Traditional manual annotation methods are inefficient and prone to errors. Existing solutions often fail to meet the requirements for high precision and efficiency, thus there is an urgent need for a high-quality image classification dataset… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Eyebrow-Makeup-Product-Image-Classification-Dataset.738k-product-classificationsproduct_store_type_classificationGenerated product names and their associated store types. Use to train store_type_classifyer