In this video, we will be learning what is hyperparameter tuning in Machine learning but before that let us see what is a Machine learning model.
A mathematical model containing a number of parameters that must be learned from the data is referred to as a machine learning model. We can fit the model parameters by using existing data to train a model.

What are hyperparameters?

Hyperparameters, on the other hand, are a different class of parameters that cannot be directly learned through routine training. Usually, they are fixed before to the start of the programme itself. These parameters describe crucial model characteristics including complexity and learning rate.

Finding the optimal combination of hyperparameters to enhance the model's performance is known as hyperparameter tuning (or hyperparameter optimization). It operates by conducting numerous trials within a single training procedure.

Hyperparameter tuning: 
https://www.geeksforgeeks.org/hyperparameter-tuning/