Gradient Descent
An optimization algorithm widely used in machine learning and neural networks to minimize a cost function, which is a measure of error or loss in the model.
Areas of application
- Machine Learning
- Artificial Intelligence
- Neural Networks
- Data Mining
- Predictive Analytics
- Computer Vision
- Natural Language Processing
- Image Recognition
Example
Imagine you’re trying to build a model that can predict the price of a house based on its size and location. The cost function would be the sum of the errors between the predicted prices and the actual prices. Gradient descent would adjust the model’s parameters to minimize this cost function, resulting in more accurate predictions.