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VERSION:2.0
PRODID:-//NextToU//EN
CALSCALE:GREGORIAN
BEGIN:VEVENT
UID:0c3fa6f3-528d-4043-8dd3-c0592ef0e548@nexttoyou
DTSTAMP:20261105T153501Z
DTSTART:20261109T150000Z
DTEND:20261109T170000Z
SUMMARY:Interpretable Machine Learning
DESCRIPTION:Some predictive machine learning models provide interpretable 
 results\, while others are black boxes. In either case\, it’s important t
 o know how and why a model made the predictions it did. This workshop wil
 l introduce tools for interpreting machine learning models and explaining
  their predictions. Topics covered include:\n\nInherently interpretable m
 odels (linear and logistic regression\, decision trees)Feature importance
 Individual conditional expectation (ICE) and partial dependence (PDP) plo
 tsLocal surrogate models (LIME)Shapley additive explanations (SHAP)\n\nAl
 l methods will be discussed at an approachable\, non-technical level and 
 demonstrated using worked examples in R and Python.\n\nRegister Now\n\nht
 tp://next-to-u.app/events/0c3fa6f3-528d-4043-8dd3-c0592ef0e548
URL:http://next-to-u.app/events/0c3fa6f3-528d-4043-8dd3-c0592ef0e548
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