Course Content

Course Content


The most basic and likely most typical approach for splitting such a dataset is to randomly sample a portion of it. For example, 80 percent of the dataset's rows may be randomly selected for training, while the remaining 20% could be used for testing.

Splitting a dataset can also help you figure out if your model is suffering from underfitting or overfitting, two extremely prevalent difficulties. Underfitting occurs when a model is unable to contain the relationships between variables.

Recommended Courses

Share With Friend

Have a friend to whom you would want to share this course?

Download LearnVern App

App Preview Image
App QR Code Image
Code Scan or Download the app
Google Play Store
Apple App Store
598K+ Downloads
App Download Section Circle 1
4.57 Avg. Ratings
App Download Section Circle 2
15K+ Reviews
App Download Section Circle 3
  • Learn anywhere on the go
  • Get regular updates about your enrolled or new courses
  • Share content with your friends
  • Evaluate your progress through practice tests
  • No internet connection needed
  • Enroll for the webinar and join at the time of the webinar from anywhere