learn-co-students / regularisation-ds

regularisation-ds

Learning objectives

By the end of the session students should be able to:

• Define regularisation
• Compare the diferent types of regularisation
• Identify situations in which regularisation could be useful
• Explain the impact of increasing/reducing regularisation hyper-parameters
• Explain how information criteria help find the best value for the regularisation hyper-parameters
• Describe the pre-processing necessary before applying regularisation
• Run regularisation applied to linear regression learners
• Compare the impact of regularisation when applied to datasets of increasing complexity/size

Resources

slides