Stokastik

Machine Learning, AI and Programming

Tag: E-commerce

Designing large scale similarity models using deep learning

Finding similar texts or images is a very common problem in machine learning used extensively for search and recommendation. Although the problem is very common and has high business value to some organisations, but still this has remained one of the most challenging problems when the database size is very large such as >50GB and we do not want to lose on precision and recall much by retrieving only 'approximately' […]

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Detecting placeholder images in e-Commerce product listings

Many times we trust sellers to upload correct product images for online products on our e-commerce platform, but due to checks in place that a product shall always accompany an image, 3rd party sellers upload stock or placeholder image in case there is no image for the product available. Problem is that although we do not want to show products without images on our website, but due to zero validation […]

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Attribute Extraction from E-Commerce Product Description

In this post we are going to look into how one can use product title and description on e-commerce websites to extract different attributes of the product. This is a very fundamental problem in e-commerce which has widespread implications for Product Search (search filters), Product Matching (matching same items from different sellers), Product Grouping (grouping items by variants such as size and color), Product Graph (relationship between products based on […]

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