"Branching Out into Isolation Forests" with guest speaker Stephanie Kirmer

For the December edition of our R-Ladies Dallas webinar series, we are excited to welcome Stephanie Kirmer as our guest speaker. She will introduce the topic of Isolation Forests for tree-based anomaly detection.

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Branching Out into Isolation Forests: Tree Based Anomaly Detection
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Abstract:
Isolation forests offer a new way to approach unsupervised anomaly detection problems, and in this talk attendees will get an end-to-end tutorial with code and visual explanations on how to apply the technique in R. Among other advantages, isolation forests offer interpretability and rapid runtime, so they are useful in business and production settings.

Bio:
Stephanie Kirmer is a Senior Data Scientist at Saturn Cloud, a platform enabling easy to use parallelization and scaling for Python with Dask. (But she still loves R as well.) Previously she worked as a DS Tech Lead at Journera, a travel data startup, and Senior Data Scientist at Uptake, where she developed predictive models for diagnosing and preventing mechanical failure. Before joining Uptake, she worked on data science for social policy research at the University of Chicago and taught sociology and health policy at DePaul University.

Slides/Code:
Stephanie's slides were prepared using the R xaringan package and are available in the following github repository in the 'r' subdirectory. Code used in her demo are also provided in the repo. You are invited to follow along during the presentation. https://github.com/skirmer/isolation_forests

Twitter: @data_stephanie

Website: http://www.stephaniekirmer.com/

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