Cross Validation In Machine Learning | Cross Validation | Machine Learning Tutorial | Simplilearn
Taha GÖÇER
About this course
This course delves into cross validation in machine learning, its importance in model evaluation, and the various methods used to implement it. Participants will explore the need for cross validation, step-by-step procedures for executing it, and hands-on demonstrations using Python code. Key types discussed include k-fold and stratified k-fold cross validation, equipping learners with practical knowledge to improve model accuracy and avoid overfitting.
What you should already know
A basic understanding of machine learning concepts and proficiency in Python programming.
What you will learn
By the end of the course, learners will gain the ability to effectively implement cross validation techniques to enhance model performance and interpret validation results.