### Among the common machine learning algorithms, which require feature scaling, and which do not?

Scaling is necessary for ML algorithms such as Neural Networks, regularized regression, SVM, KNN

- Machine Learning 101 (30)
- Statistics 101 (38)
- Supervised Learning (108)
- Regression (36)
- Classification (46)
- Logistic Regression (10)
- Support Vector Machine (10)
- Naive Bayes (4)
- Discriminant Analysis (5)
- Classification Evaluations (9)

- Classification & Regression Trees (CART) (23)

- Unsupervised Learning (46)
- Clustering (17)

- Regularization (6)
- Deep Learning (23)
- Data Preparation (43)
- General (5)
- Standardization (6)
- Missing data (7)
- Textual Data (16)
- Dimensionality Reduction (9)

Scaling is necessary for ML algorithms such as Neural Networks, regularized regression, SVM, KNN

Feature scaling is a data pre-processing technique that transforms the original support of a variable to a different scale.

Find out all the ways

that you can