Easiest Guide to K-Fold Cross Validation | Explained in 2 Minutes!
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๐ฅ K-Fold Cross Validation explained in 2 minutes! In this video, we talk about one of the best methods for hyperparameter tuning and assessing the generalizability of the model called K-Fold Cross-Validation. Unlike simple train-test-validation split, this method runs the training process with different subsets for training and validating, and then averages the results, making the performance estimation more reliable. While it has lots of advantages, it is not perfect! Suppose you have a large dataset and a complex model. It iโฆ
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Chapters (10)
Introduction.
0:11
Train-Test-Validation split.
0:40
The main assumption of train-test-validation split.
1:10
What about small datasets?
1:18
K-Fold Cross Validation Explained.
1:48
Advantages of K-Fold Cross Validation.
2:05
Disadvantage of K-Fold Cross Validation.
2:15
Large vs. Small Datasets.
2:25
Do this to get up to 50% additional accuracy score! :)
2:31
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