many
trees independently, each randomized in a different way, and
then averages their predictions. Gradient boosting on the
other hand builds trees one by one in a sequential manner,
with each tree requiring the results of previous trees.
Often, Gradient boosting is done with very small trees, or
even decision stumps, which is trees of depth one, so a
single split.

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class: center, middle
# Boosting (in General)

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 - “Meta-algorithm” to create strong learners from weak learners.
 - AdaBoost, Gentl