Zillow面經

Zillow的HR透過LinkedIn聯絡

1.1  Cosine similarity, very sparse, long vector

What datastructures to use? Calculate Cosine similarity efficiently.

A.     Dictionary<long, float>,O(min(m,n))

B.     Tuple<long, float>[], binary search O(mlog(n))

1.2  Word count for all wiki pages

A.     Assume data already downloaded –distribute pages across all machines, do local count and aggregate at the end

B.     How to download – Task queue,task state: Active/Picked/Completed, handle single point failure

2.1 Gradient descent to update weights forlinear regression, pseudo-code

2.2 Model performs well on train andvalida

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between new heap every time or cleaning and reusingexisting heap?

What if data is too big to fit into memory? Distribute tomultiple machines (communication overhead) or use generator.

沒什麼太多coding問題,比較多ML或System design的問題

面完時還挺有信心的,最後還有見到Senior Director,可是一個禮拜後收到感謝函QQ

稍微抱怨一下,Zillow居然連lyft或Uber的費用都不給報帳,雖然有免費停車

感谢！很有用的信息，最近也要面试zestimate，谢谢分享