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Anomaly Detection in transactions volumes
The objective of the project is to investigate how machine learning techniques can be used to detect anomalies in volumes of transactions. This requires the student to conduct a literature review about the topic as well as experimenting with a subset of selected machine learning techniques. The results from the research could help the partner organization in improving in place mechanisms used to detect anomalies in volume of transactions.
Faculty Supervisor:
Anthony Bonner
Student:
Partner:
Ethoca Technologies
Discipline:
Computer science
Sector:
Information and cultural industries; Professional, scientific and technical services
University:
University of Toronto
Program:
Accelerate
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