PinnedValerie CareyinTowards Data ScienceWhat (Not) To Say When Your Client Questions Your ResultsUse these pivotal moments to build trust and understandingJul 19, 20225Jul 19, 20225
Valerie CareyinTowards Data ScienceVisualizing Stochastic Regularization for Entity EmbeddingsA glimpse into how neural networks perceive categoricals and their hierarchiesAug 61Aug 61
Valerie CareyinTowards Data ScienceData Disruptions to Elevate Entity EmbeddingsInjecting random values during neural network training can help you get more from your categoricalsJun 4Jun 4
Valerie CareyinTowards Data ScienceNo Label Left Behind: Alternative Encodings for Hierarchical CategoricalsSeeking a system that works for current and future codesMay 17May 17
Valerie CareyinTowards Data ScienceExploring Hierarchical Blending in Target EncodingWhen can code hierarchies improve target encoding for high-cardinality categorical features?Apr 181Apr 181
Valerie CareyinTowards Data ScienceSHAP vs. ALE for Feature Interactions: Understanding Conflicting ResultsModel Explainers Don’t Produce ExplanationsOct 2, 20231Oct 2, 20231
Valerie CareyinFanfareBook Discussion| AI 2041: Ten Visions for Our FutureExceptional young men, lovelorn young women, and botsMay 14, 20221May 14, 20221
Valerie CareyinTowards Data ScienceAI Integrity: Leadership Lessons from Other IndustriesDo other fields make mistakes better?Feb 4, 20221Feb 4, 20221
Valerie CareyinTowards Data ScienceAI Integrity: Planning Ahead to Do The Right ThingHow to prepare for inevitable mistakesNov 30, 20211Nov 30, 20211