What context can I use each word in?
Learn when and how to use these words with these examples!
normalization
Example
We need to perform normalization on the dataset before training the model. [normalization: noun]
Example
The values were normalized between 0 and 1 to ensure consistency. [normalized: past participle]
regularization
Example
We applied L2 regularization to the model to prevent overfitting. [regularization: noun]
Example
The regularization term helped to reduce the model's complexity and improve its accuracy. [regularized: past participle]
Good things to know
Which word is more common?
Normalization is more commonly used than regularization in data preprocessing and analysis. It is a fundamental step in preparing data for machine learning models. Regularization, on the other hand, is a more advanced technique used during model training to improve performance.
What’s the difference in the tone of formality between normalization and regularization?
Normalization is a more general term and can be used in various contexts, including informal ones. Regularization is a more technical term and is typically used in formal or academic settings related to machine learning and data science.
