Difference between deviation and variance in deep learning

Explain a

** deviation （Bias）: ** It describes the predicted value （ Estimated value ） The gap between expectations and reality . The bigger the deviation , The more deviated from the real data , The representation in the figure below is the distance from the data point to the center of the red circle .
** variance （Variance）：** It describes the range of changes in the predicted values , The degree of dispersion , That is, the distance from its expectation . The greater the variance , The more scattered the data points are .

Explain two

** deviation （Bias）：** In deep learning , It represents the size of the training error on the training set .
** variance （Variance）：** In deep learning , It represents the difference between the error on the training set and the error on the verification set , The greater the gap between , The higher the variance , The more fitting is formed .