What are the differences between vectorization and normalization?

What are the differences between vectorization and normalization?

Vectorization refers to the process of converting data into a vector format, while normalization is about scaling data to a specific range.

Can you give me examples of when to use each?

Sure! Use vectorization when you need to represent text or categorical data numerically. Use normalization when you want to ensure that features contribute equally to distance calculations.

Are there specific algorithms that require normalization?

Yes, algorithms like k-means clustering and gradient descent benefit from normalization to improve convergence and accuracy.

What happens if I don't normalize my data?

If you don't normalize your data, some features may dominate others, leading to biased results and poor model performance.