The Right and the Wrong Way to Do Cross-validation

  You might wonder why do we need cross validation in the first place itself. Let’s explain that first. Normally, the generalization performance of a machine learning algorithm depends on its prediction capability on an independent test data. This assessment is of utmost importance to us. Cross Validation is such a model validation technique...

Hyperparameter Optimization and Why is it important?

A machine learning model consists of various parameters that need to be learned from the data. The crux of Machine learning is fitting a model to the data. This process of training a model with existing data to fit the model parameters, is called model training. Hyperparameters refer to another kind of parameters that...