Chap. 3

Question 1

what is Cross-validation?

Answer 1

to evaluate a model on unseen data by spliting the dataset into a number of training and validation sets and to evaluate the performance of the model on the these sets.

This will help with
1- Best hyper-parameters
2- Avoid overfitting the model to a single training data.

Question 2

what is Hyper-parameter?

Answer 2

Hyper-parameter tuning is a process of finding the optimal values for the parameters that control the behavior of the model. by experimenting with different values for the hyper-parameters such as the learning rate, regularization, and number of latent factors to find the combination that results in the best performance.