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Publicly available e-commerce datasets for a Machine Learning experimentation

Machine learning presents a huge growth opportunity for online retailers. With machine learning, eCommerce companies can boost sales, reduce waste, and increase overall efficiency while actively engaging with consumers.

Here is a short list of publicly available data that you can experiment with:

• eCommerce Item Data: Very useful if you want to experiment a recommandation system based on the product description.
• Zalando Fashion MNIST: This Dataset intend to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.
• Innerwear Data from Victoria’s Secret and Others: The datasets were created by extracting data from the popular retail sites via PromptCloud’s data extraction solutions. It contains 126 columns, like product_name, price, description, etc..
• Electronic Products and Pricing Data: This is a list of over 7,000 electronic products with pricing information across 10 unique fields provided by Datafiniti’s Product Database. The dataset also includes the brand, category, merchant, name, source, and more.
• Amazon — Ratings (Beauty Products): This is a dataset related to over 2 Million customer reviews and ratings of Beauty related products sold on their website.