Topic: "Introduction to Fraud and Anomaly Detection" Speaker: Dr. Aric LaBarr, Associate Professor in the Institute for Advanced Analytics
Dr. Aric LaBarr is passionate about helping people solve challenges using their data. There he helps design the innovative program to prepare a modern workforce to wisely communicate and handle a data-driven future at the nation's first Master of Science in Analytics degree program. He teaches courses in predictive modeling, forecasting, simulation, financial analytics, and risk management. Previously, he was Director and Senior Scientist at Elder Research, where he mentored and led a team of data scientists and software engineers. As director of the Raleigh, NC office he worked closely with clients and partners to solve problems in the fields of banking, consumer product goods, healthcare, and government. Dr. LaBarr holds a B.S. in economics, as well as a B.S., M.S., and Ph.D. in statistics - all from NC State University.
Develop good features (recency, frequency, and monetary value as well as categorical transformations) for detecting and preventing fraud
Identify anomalies using statistical techniques like z-scores, robust z-scores, Mahalanobis distances, k-nearest neighbors (k-NN), and local outlier factor (LOF)
Identify anomalies using machines learning approaches like isolation forests and classifier adjusted density estimation (CADE)
Visualize these anomalies identified by the above approaches
Basic introduction to decision trees (this isn't required, but helpful for understanding)
Basic introduction to classification models like logistic regression, decision trees, etc. (this isn't required, but helpful for understanding)
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ODSC brings together the open-source and data science communities with the goal of helping its members learn, connect and grow.
The focus of this Meetup group is to allow ODSC to work with Meetup groups, non-profits, and other organizations to present informative lectures, workshops, code sprints and networking events to help grow the use of open source languages and tools within the data science and data-centric community. As such, our specific goals are:
1. Build a collaborative group to work with other Meetup groups, non-profits, and other organizations.
2. Promote the use of open source languages and tools amongst data scientists and others.
3. Host educational workshops.
4. Spread awareness of new open source languages and tools that can be used in data science.
5. Contribute back to the open-source community.
Who is this meetup for?
• Data engineers, analysts, scientists, and other practitioners
• R, Python and other software engineers who work with data or want to learn
• Data visualization developers and designers
• Non-technical team leads, executives, and other decision-makers from data-centric startups and large companies looking to utilize open-source tools