Gradient Algorithms Repository

This repository contains a collection of gradient algorithms implemented in various programming languages. Gradient algorithms are widely used in optimization and machine learning tasks for finding the minimum or maximum of a function.

Algorithms Included

1. Gradient Descent
2. Stochastic Gradient Descent
3. Mini-Batch Gradient Descent
4. Conjugate Gradient Descent
5. Momentum-Based Gradient Descent
6. Nesterov Accelerated Gradient Descent
7. AdaGrad
8. RMSProp
9. Adam
10. AdaDelta

Usage

Each algorithm is implemented in python as a separate file. The algorithms can be used by importing the specific file or module into your project.

Python

To use the Python implementations, follow these steps:

1. Clone the repository:

git clone https://github.com/abomine/gradient.git

2. Import the desired algorithm in your Python script:

from gradient import gradient_descent

# Use the gradient descent algorithm
gradient_descent()

3. Customize the algorithm parameters and integrate it into your code as needed.

License

This repository is licensed under the MIT License. Feel free to use the code for personal or commercial purposes.