AI News, Massive Open Online Course: "Process Mining: Data science in Action"

Massive Open Online Course: "Process Mining: Data science in Action"

The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically).

Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, understanding the browsing behavior of customers using a booking site, analyzing failures of a baggage handling system, and improving the user interface of an X-ray machine.

The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically).

Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, understanding the browsing behavior of customers using a booking site, analyzing failures of a baggage handling system, and improving the user interface of an X-ray machine.

Coursera Course "Process Mining: Data science in Action"

To register visit About the Course Data science is the profession of the future, because organizations that are unable to ..

Customer Segmentation in Python - PyConSG 2016

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Process Mining and Predictive Process Monitoring

Process Mining and Predictive Process Monitoring are two major trends in the field of Business Process Management. This talk gives an overview of ...

A Machine Learning Approach to Log Analysis - Ianir Ideses - DevOpsDays Tel Aviv 2016

Detecting Network Intrusions With Machine Learning Based Anomaly Detection Techniques

Machine learning techniques used in network intrusion detection are susceptible to “model poisoning” by attackers. The speaker will dissect this attack, analyze ...

Anomaly Event Detection using Spatio-Temporal Motion Patterns

The importance of anomaly event detection is growing up in recent years due to the improvement of security and safety in video surveillance systems. We focus ...

Process Mining for Learning Analytics

Animating students' learning behaviours as reflected by data from a Learning Management System through the application of process mining techniques.