Practice Session 6
In this video, I have demonstrated cross validation through an example and then showed you how to implement it in code using the Sklearn library. Cross validation is a powerful technique for evaluating machine learning models by splitting data into training and test sets multiple times. This ensures that each set of data is used as both a training set and a testing set.
Video
Objectives:
- Explaining Cross Validation
- Cross Validation with scikit-learn
Highlights:
- Remaking walkwithfasta course ( https://walkwithfastai.com/ )
- Lesson Three - Part 2: Cross Validation
Resources:
- https://drive.google.com/file/d/116YbPfaYli3XilPxRKloYd3sZmKT-ozT/view?usp=sharing
- https://docs.google.com/presentation/d/1DMQg-yISwmR_TwGcmVAfSCG0OJPUND2T/edit#slide=id.p1