The gradient is a vector of partial derivatives that points in the direction of steepest increase.
What Is Gradient?
The gradient is a vector of partial derivatives that points in the direction of steepest increase.
Examples of Gradient
1
For f=x²+y², ∇f=(2x,2y).Formula and Key Points
Formula / rule
∇f=(∂f/∂x₁,…,∂f/∂xₙ)
- Know the definition and standard notation for Gradient.
- Be able to recognise or compute gradient in a small example.
- Connect the concept to nearby topics in the same subject before using it in larger CSE problems.
Why This Matters in Computer Science
Used in optimization, simulation, graphics, machine learning, control systems and numerical computing. In machine learning, gradients guide parameter updates that reduce a loss function.
Related Math Terms
Gradient: Frequently Asked Questions
What is Gradient?
The gradient is a vector of partial derivatives that points in the direction of steepest increase.
Why is Gradient useful in computer science?
Used in optimization, simulation, graphics, machine learning, control systems and numerical computing. In machine learning, gradients guide parameter updates that reduce a loss function.