Optimisation using Gradient Descent #
Gradient descent is an optimisation algorithm used to train ML and neural networks.
- Gradient descent updates parameters by moving opposite the gradient.
Trains ML models by minimising errors:
- between predicted and actual results
- by iteratively adjusting its parameters
- moves step‑by‑step in the direction of the steepest decrease in the loss function, it helps ML models learn the best possible weights for better predictions
Types of Gradient Gescent learning algorithms #
- Batch gradient descent
- Stochastic gradient descent
- Mini-batch gradient descent