Detect "Zero-Day" anomalies in cloud infrastructure logs.

This project applies data wrangling techniques to a retailer's data set of online orders. These techniques include determining and removing syntactical as well as semantic anomalies, removing outliers and imputing missing values using basic machine learning.

Wrangling a dataset that contains transactional retail data from an online electronics store (DigiCO) in Melbourne, Australia.