Machine Learning Fundamentals Bias & Variance | Bias and Variance Clearly and Easily Explained

Bias & Variance are the two basic fundamentals of machine learning.
so, it is important to understand the concept.

Bias is the simplifying assumptions made by the model to make the target function easier to approximate.

Variance is the amount that the estimate of the target function will change given different training data. The trade-off is tension between the error introduced by the bias and the variance.

Explained