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You are an ML engineer at a regulated insurance company. You are asked to develop an insurance approval model that accepts or rejects insurance applications from potential customers. What factors should you consider before building the model?
Suggested Answer: B
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13 comments · newest first
DE
Deonna
12 months ago
Totally agree, reproducibility is a must!
GE
Geraldine
12 months ago
Redaction isn't really relevant for this, right?
JA
Jaclyn
1 year ago
Wait, are we really talking about federated learning here? Sounds complicated!
HA
Haydee
1 year ago
I think traceability is super important too.
YV
Yvonne
1 year ago
Definitely need to consider explainability!
OZ
Ozell
1 year ago
I vaguely recall that redaction might be relevant for data privacy, but I can't remember how it fits into the model-building process.
LI
Linn
1 year ago
I’m leaning towards option B because reproducibility seems crucial, but I’m a bit confused about the differences between the options.
HU
Hui
1 year ago
I practiced a similar question where traceability was emphasized, so I feel like it might be a key factor here too.
HO
Howard
1 year ago
I think I remember that explainability is really important for models in regulated industries, but I'm not sure about the other factors.
KE
Kerry
1 year ago
I'm pretty confident in my Java knowledge, so I think I can spot the right answer here. Let me take a closer look.
JO
Josefa
1 year ago
Caustic was mentioned in a similar example we did in class, but I'm still torn between that and the other options.
RE
Reynalda
1 year ago
This is a tricky one. I'm debating between the custom list view and the Salesforce Console 'History' component. Both seem like they could work, but I'll need to weigh the details of each to decide which is the better recommendation.
MA
Maryann
1 year ago
Okay, I think I've got this. The key here is the concept of "fault tolerance" - the ability of a system to continue functioning even when one of its components fails. That sounds like the most relevant answer choice to me.