Hi fellow leetcoders,

I've received some questions concerning the bias and variance, which are actually important notions that are often encountered during the interview. Therefore, as a follow-up for the Machine Learning 101 card, I decided to write an article to explain the intuition behind these two notions. Hope this might be of help to your questions or doubts.

As a reminder, you can find the article at the end of the second chapter, right after the article on Underfiitting VS. Overfitting. Actually, the bias and variance provide a more accurate perspective to understand the phenomenons of underfitting and overfitting.

As usual, feel free to leave a comment if you have any doubt.