new methods; eigenvalue. condition number implemetation

eigenvalue module, readme and demo update. condition number implemented in linalg.py

README.md

@@ -43,6 +43,7 @@ This package comes with a set of Jupyter notebooks designed as a structured tuto
    - Examples with `numethods.orthogonal`.
 
 4. [Tutorial 4: Root-Finding Methods](tutorials/tutorial4_root_finding.ipynb)
+
    - Bisection method.
    - Fixed-point iteration.
    - Newton’s method.
@@ -52,10 +53,10 @@ This package comes with a set of Jupyter notebooks designed as a structured tuto
    - Examples with `numethods.roots`.
 
 - [Polynomial Regression Demo](tutorials/polynomial_regression.ipynb)
-  - Step-by-step example of polynomial regression.
-  - Shows how to fit polynomials of different degrees to data.
-  - Visualizes fitted curves against the original data.
-  - Uses `PolyFit` from `numethods.fitting`.
+
+- Step-by-step example of polynomial regression.
+- Shows how to fit polynomials of different degrees to data.
+- Visualizes fitted curves against the original data.
 
 ---
 
@@ -98,6 +99,13 @@ This package comes with a set of Jupyter notebooks designed as a structured tuto
 - **Second derivative**: `SecondDerivative`
 - **Richardson extrapolation**: `RichardsonExtrap`
 
+### Eigenvalue methods
+
+- **Power Iteration** (dominant eigenvalue/vector): `PowerIteration`
+- **Inverse Power Iteration** (optionally shifted): `InversePowerIteration`
+- **Rayleigh Quotient Iteration**: `RayleighQuotientIteration`
+- **QR eigenvalue iteration** (unshifted, educational): `QREigenvalues`
+
 ### Matrix & Vector utilities
 
 - Minimal `Matrix` / `Vector` classes