Artificial Intelligence, Machine Learning, Data, Data Science, Predictions.
the data scientist’s toolkit. The Need for Regularization Before we delve into the specifics of regularization techniques, let’s understand why they are crucial. Traditional regression models, such as linear regression, aim to minimize the sum of squared errors between predicted and actual values.