Why It Matters
A model that is accurate on your test set can still be unusable — because it is illegal to deploy without an explanation, because it is right for a reason that will not survive next quarter, or because nobody will act on a number they cannot interrogate.
Global Methods
Global methods describe how a model behaves across the whole dataset: which features it relies on, and what shape each relationship takes.
Local Methods
Local methods explain a single prediction: not "what does this model rely on" but "why did this row come out the way it did". That is the question a declined applicant, a flagged transaction, or a debugging session actually asks.
Pitfalls
Explanation methods produce a plot for any model, on any data, whether or not the result means anything. Knowing when the plot is lying is most of the skill.