Apparel Recommendation workshop - Amazon

Problem Statement:

• Product recommendations are the alternative way of navigating through the online shop. Showing similar products to the user which user is searching for.

• Build a recommendation engine which suggests similar products to the given product in any e-commerce websites using NLP techniques for Text Semantics based product similarity and deep learning techniques for deep learning based visual product similarity.

Objective:

• The recommendation engine, uses information about 1,80,000 products and each product will have multiple features named.
• We will try multiple techniques using text/title and image to recommend similar products/items

Each product/item has 19 features in the raw dataset out of these 19 features, we will be using only 6 features

1. asin ( Amazon standard identification number)
2. brand ( brand to which the product belongs to )
3. color ( Color information of apparel, it can contain many colors as a value ex: red and black stripes )
4. product_type_name (type of the apperal, ex: SHIRT/TSHIRT )
5. medium_image_url ( url of the image )
6. title (title of the product.)
7. formatted_price (price of the product)

Reference :

1. https://www.appliedaicourse.com/course/13/workshop