Radek Zaworski

Radek Zaworski

Data Scientist at Snowdog

Approaches to augmenting data and challenges with limited datasets

Data augmentation is a technique used to increase the amount of data available for machine learning models when faced with limited datasets. In the field of eCommerce, where R&D teams are developing new technologies to improve user experience, this is a common issue. With limited data available, training machine learning models to categorize product images can be difficult. This is where data augmentation techniques come in, allowing for the creation of new synthetic data from the existing dataset to improve the performance of the model. In this blog post, we will explore the different approaches to data augmentation and the challenges that arise when dealing with limited datasets in eCommerce.