K-fold cross validation is the practice by which we separate a large data set into smaller...
00:55
K-fold cross validation is the practice by which we separate a large data set into smaller...
00:55
Stratified sampling provides a mechanism by which to split a larger dataset into smaller pieces....
00:59
Stratified sampling provides a mechanism by which to split a larger dataset into smaller pieces....
00:59
Boosting is also an ensemble meta-algorithm, like boosting. However, in boosting we teach a large...
00:51
Boosting is also an ensemble meta-algorithm, like boosting. However, in boosting we teach a...
00:51
Bagging is an ensemble meta-algorithm. Basically, we take some number of estimators (usually...
00:50
Bagging is an ensemble meta-algorithm. Basically, we take some number of estimators (usually...
00:50
Bias, Variance, and the Bias-Variance Tradeoff
The bias-variance trade-off is a key problem in your model search. While bias represents how well...
01:57
Bias, Variance, and the Bias-Variance Tradeoff
The bias-variance trade-off is a key problem in your model search. While bias represents how...
01:57
The concept of empirical risk minimization drives modern approaches to training many machine...
00:38
The concept of empirical risk minimization drives modern approaches to training many machine...
00:38
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