8.2 Intuition behind bias and variance (L08: Model Evaluation Part 1)
30:51
8.3 Bias-Variance Decomposition of the Squared Error (L08: Model Evaluation Part 1)
21:17
8.1 Intro to overfitting and underfitting (L08: Model Evaluation Part 1)
6:36
Machine Learning Fundamentals: Bias and Variance
10:25
When is a Biased Estimator Better? A Look at Ratio Estimators
20:27
Regularization Part 1: Ridge (L2) Regression
52:45
Strategy for the NN model bias and variance by Mr. Ashutosh Kumar Jha
25:05
6.1 Intro to Decision Trees (L06: Decision Trees)
18:49