Marvell Semiconductors Machine Learning Engineer Intern Interview Questions and Answers

Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.

• Bias is error introduced by approximating a real-world problem, leading to underfitting.

• Variance is error introduced by modeling the noise in the training data, leading to overfitting.

• High bias and low variance models are simple and may not capture the underlying patterns in the data.

• High variance and low bias models are ...read more