A comparison of machine learning techniques for the classification of products for CPI production.
In this project the efficacy and usability of traditional machine learning techniques and deep learning techniques in classifying items of clothing is researched. A dataset of around 320.000 items of clothing and shoes was used in these experiments. These products were classified into 319 categories based on their brand, an ID code and a short description.
