Basic Math Concepts – Standardization in Neural Networks
| Concept | Why It’s Needed |
|---|---|
| Mean | To center the feature |
| Standard Deviation | To scale it to unit variance |
| Sigmoid | To squash outputs in neural nets |
| Derivative | For backpropagation (chain rule) |
| Basic Linear Algebra | Weight updates and dot products |
| Squared Error | Loss calculation |
Standardization in Neural Networks – Summary
