Applied Machine Learning for Anomaly Detection on Equipment
09:00-16:30 January 26

Full day
Intermediate level

Details

Equipment failure in heavy industry (maritime, oil and gas, mining...) accounts for millions of dollars in downtime and repairs annually. In this workshop, we will go through a use case of detecting non-normal equipment behavior using sensor data. You will be training models on historic data and have to deploy these models into a cloud environment to make predictions on live stream data.


Outcome

This is an opportunity to familiarize yourself with end-to-end unsupervised Machine Learning in a production environment. You will also have a chance to productionize your trained Machine Learning model by deploying it into the cloud.


Prerequisites

  • Intermediate level in ML and data science
  • Working knowledge in open source Python Machine Learning stack is preferred, but R and Matlab users welcome
  • No business knowledge or expertise required
  • Only Python can be deployed to the cloud

Organizers

Alexandra Gunderson

Data Scientist, Arundo Analytics