Exam Professional Machine Learning Engineer topic 1 question 57 discussion

Ans: C (See https://developers.google.com/machine-learning/problem-framing/framing#quantify-it; though it's just an example.) (A) The absolute number of likes shouldn't be used because no information about subscribers or visits to the website is provided. The number may vary. (B) Clickbait videos are a subset of uploaded videos. Using them is an improper criterion. (D) The coefficient should reach 1. (Ref:https://arxiv.org/pdf/1510.06223.pdf)

The answer is A. Because the number of previous user likes is the only feature available on inference time (when the video has just been uploaded). Watch time and clicks are unavailable at inference time and should not be used for training!

C) Watch time

Went with C

ans: C In this type of questions, I think a good idea is trying to copy already existing solutions. For this case, YouTube cares a lot about watchtime. In a previous question, Amazon implemented "Usually buy together" for maximizing profit.

Must be C

watch time among all other options is the most KPI to rely on

I think this is B. The question specifies "popular" and also that "newly uploaded" videos need prioritising. C is therefore wrong because you don't have that metric until 30 days has passed from upload time. "Click through rate" is one measure of popularity, so it fits, and is instant.

C looks correct.

ANS: C D is wrong. Pearson's Correlation Coefficient is a linear correlation coefficient that returns a value of between -1 and +1. A -1 means there is a strong negative correlation +1 means that there is a strong positive correlation 0 means that there is no correlation