K-fold Cross Validation is a powerful technique used in machine learning to assess the performance of a model. It helps in reducing bias, ensuring better generalization, and providing a more reliable estimate of model performance. In this video, Varun sir will explore the key points of K-fold Cross Validation, including how it works, its advantages, and how it can improve the accuracy of your machine learning models.
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Timestamps:
00:00 - What is Cross-Validation?
01:00 - Model
05:38 - Features of K-fold Cross Validation
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