There is a huge opportunity of Machine Learning use cases to improve incident management process and scope for automating multiple task including incident assignment.Here analyze incident event data to identify ML use cases. Datasets is from Dataset is from UCI ML repository.
No extra libraries needs to be installed as all the libraries used here comes up wwith the Anaconda distribution with Python3.6.
Incident managment has huge oppertunity around ML use case as these get generated from huge event log data. Here I thought to analyze Incident event data to see what hidden patterns will help us to come up with impactful ML use case.
The jupyter notebook is the only code file that has all the code.
Fork the repository and contribute on other ideas to analyze for more ML use case around incident managent.
Dataset is from UCI ML repository in which event log was extracted from data gathered from the audit system of an instance of the ServiceNow platform used by an IT company and enriched with data loaded from a relational Dataset(https://archive.ics.uci.edu/ml/datasets/Incident+management+process+enriched+event+log)