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Log data is everywhere. You have petabytes of it, with streams collected from every device. But are you using it to learn more about your users or your system? In this presentation we will walk through leveraging pattern mining along with ML techniques to identify frequent patterns that exist in your logs. We will apply these techniques to a real-world application, developing the 'Frequently Bought Together' feature we have all seen on Amazon.
After going through the intuition in the frequent pattern mining algorithm, the instructor will show how you don't need to be an expert in order to get results quickly. The entire presentation will be delivered from an iPython Notebook and written in Python, using Dato for performing the frequent pattern mining, model training, and deployment of the frequently bought together service.
Basic understand of data mining and intermediate level or higher in Python.