juniorLinear Regression
What is gradient descent in Linear Regression?
Updated May 16, 2026
Short answer
Gradient descent is an optimization algorithm used to minimize the cost function.
Deep explanation
It iteratively updates model parameters in the direction of the negative gradient of the loss function. This reduces error step by step until convergence.
Real-world example
Training predictive models like price forecasting systems.
Common mistakes
- Using too high learning rate causing divergence.
Follow-up questions
- What happens if learning rate is too small?