🎯 2D Gradient Descent Visualizer
Explore the journey of gradient descent as it minimizes complex 2D functions in real-time.
Initial X:
5
Initial Y:
5
Learning Rate:
0.1
Steps:
Speed (ms/step):
200
ms
Function:
f(x, y) = x² + 2y²
f(x, y) = x² + y²
f(x, y) = x² + sin(y)
f(x, y) = 2x² + y²
f(x, y) = 20 + x² + y² - 10(cos(2πx) + cos(2πy))
f(x, y) = -20e^(-0.2√(0.5(x² + y²))) - e^(0.5(cos(2πx) + cos(2πy))) + 20 + e
Custom Function
f(x, y):
∂f/∂x:
∂f/∂y:
Run Gradient Descent