Highlighted by Seqian Wang
From I interviewed at five top companies in Silicon Valley in five days, and luckily got five job offers by Xiaohan Zeng
Make sure you understand basic concepts such as bias-variance trade-off, overfitting, gradient descent, L1/L2 regularization，Bayes Theorem，bagging/boosting，collaborative filtering，dimension reduction, etc. Familiarize yourself with common formulas such as Bayes Theorem and the derivation of popular models such as logistic regression and SVM. Try to implement simple models such as decision trees and K-means clustering. If you put some models on your resume, make sure you understand it thoroughly and can comment on its pros and cons.