Applied Machine Learning on UCI Online Retail Dataset

This repository compares machine learning algorithms using the Online Retail dataset from UCI ML Repository.

Data

The used data is a transactional dataset which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers.

The dataset contains following features:

• InvoiceNo: A 6-digit integral number uniquely assigned to each transaction. If this code starts with letter 'c', it indicates a cancellation.
• StockCode: A 5-digit integral number uniquely assigned to each distinct product.
• Description: Product (item) name.
• Quantity: The quantities of each product (item) per transaction.
• InvoiceDate: The day and time when each transaction was generated.
• UnitPrice: Product price per unit in sterling.
• CustomerID: A 5-digit integral number uniquely assigned to each customer.
• Country: The name of the country where each customer resides.

Example plots

Clustering customers by recency, frequency and monetary value (RFM)

T-SNE plot of product description embeddings embeddings

Sales forecasting