i dont mean to be so off topic but does any of you know a trick to get back into an Instagram account? I somehow lost my account password. I appreciate any help you can give me
Totally random flow of thought..Nothing makes sense till 13 minutes where he mentions Trie. K-means clustering to get Coen brother fan, prefix table with all possible strings - these things show that you don't understand ML at all.
There was barely any ML related discussion in the answer No discussion on metrics or evaluation When interviewer pointed out sparsity of user profile, the answer was surprisingly worse than original There wasn't any discussion on once you get candidates matched from Trie, how would they score it using user profile When asked on scalability, the answer was far too focussed on the feature set scalability
Hi, could you elaborate on 12:02 feature expansion? A little lost on Dan's explanation. Who decides on which new feature to include out of the thousands? thanks
Jay - I would like you to be the person telling answers in some cases. Your knowledge is very good and would love u see this in parallel with the guests
His answers are very random
i dont mean to be so off topic but does any of you know a trick to get back into an Instagram account?
I somehow lost my account password. I appreciate any help you can give me
@Jedidiah Wesley Instablaster =)
Totally random flow of thought..Nothing makes sense till 13 minutes where he mentions Trie. K-means clustering to get Coen brother fan, prefix table with all possible strings - these things show that you don't understand ML at all.
The positive comments in the comments section are extremely baffling. This is one of the worst ML Design answers I've ever heard in my life.
Hey Stephen, would you like to come on the UA-cam channel for a mock interview? Please reach out and let me know.
@@iqjayfeng you know what, sure, why not
@@StephenRoseDuo Did you ever go on? I wanna see!
There was barely any ML related discussion in the answer
No discussion on metrics or evaluation
When interviewer pointed out sparsity of user profile, the answer was surprisingly worse than original
There wasn't any discussion on once you get candidates matched from Trie, how would they score it using user profile
When asked on scalability, the answer was far too focussed on the feature set scalability
I was also confused about the scalability part.
Jay, this is awesome please don't stop making these videos!!
You got it!
Those boardgames though...
Hi, could you elaborate on 12:02 feature expansion? A little lost on Dan's explanation. Who decides on which new feature to include out of the thousands? thanks
Hi, Is this supposed to be an interview for an entry level job or a senior level one? Great job on the videos either way!
Jay - I would like you to be the person telling answers in some cases. Your knowledge is very good and would love u see this in parallel with the guests
8:00 bro, that'll help develop the priors for his Max likelihood estimate
Thanks Jay, where do you find these interview questions from big tech companies?
We source them from our network! Members at Interview Query and also people we know from FAANG
This is amazing .
Wow the guy answering is very very good in algorithms and broad spectrum