This repository contains a collection of data structures and algorithms implemented in various programming languages. It is designed to help learners understand key concepts through hands-on examples. Contributions and improvements are welcome!
Stochastic Gradient Descent updates the model's parameters by calculating the gradient of the loss function for a single training example (or a small batch), rather than the entire dataset. This makes it computationally efficient but can lead to noisy updates
Idea Title
Stochastic Gradient Descent (SGD)
Idea Description
Stochastic Gradient Descent updates the model's parameters by calculating the gradient of the loss function for a single training example (or a small batch), rather than the entire dataset. This makes it computationally efficient but can lead to noisy updates
Potential Benefits
Implementation Suggestions (Optional)
No response