Metadata-Version: 2.1
Name: gradient-descent
Version: 0.0.3
Summary: Package for applying gradient descent optimization algorithms
Home-page: https://github.com/DanielDaCosta/optimization-algorithms
Author: Daniel da Costa
Author-email: daniel.pereiracosta@hotmail.com
License: UNKNOWN
Description: # gradient-descent
        
        gradient-descent is a package that contains different gradient-based algorithms, usually used to optimize Neural Networks and other machine learning models. The package contains the following algorithms:
        
        - Gradients Descent
        - Momentum
        - RMSprop
        - Nasterov accelerated gradient
        - Adam
        
        The package purpose is to facilitate the user experience when using optimization algorithms and to allow the users to have a better intuition about how this *black-boxes* algorithms works.
        
        This is an open-source project, any feedback, improvement ideas, and contributors are welcome.
        
        ## Installation
        
        **Dependencies**
        
        - Python (>= 3.6)
        - NumPy (>= 1.13.3)
        - Matplotlib (>=3.2.1)
        
        **User installation**
        
        ```
        pip install gradient-descent
        ```
        
        ## Development
        
        All contributors of all levels are welcome to help in any possible away. 
        
        **Souce Code**
        
        ```
        git clone https://github.com/DanielDaCosta/gradient-descent.git
        ```
        
        **Tests**
        
        ```
        pytest tests
        ```
        
        **TO DO**
        
        The package is still on its early days and there are a lot of improvements to make:
        
        - [ ] Build new optimization algorithms
        - [ ] Extend its use for multivariable functions
        - [ ] New ideas of functions for better usability
        - [ ] Improve Documentation
        
        # Acknowledgements
        
        First of all I would like to thank Hammad Shaikh by his well documented and very well explained GitHub repository [Math of Machine Learning Course by Siraj](https://github.com/hammadshaikhha/Math-of-Machine-Learning-Course-by-Siraj/blob/master/Gradient%20Descent%20for%20Optimization/Gradient%20Descent%20for%20Optimization.ipynb)
        
        I would like to appreciate the help of the following contents and articles in the package development:
        
        - [Optimizing Gradient Descent](https://ruder.io/optimizing-gradient-descent/) by Sebastian Ruder
        - [Optimization Techniques for Gradient Descent](https://www.geeksforgeeks.org/optimization-techniques-for-gradient-descent/?ref=rp) by www.geeksforgeeks.org website
        - [optimization_algos](https://github.com/idc9/optimization_algos) GitHub repository by Iain Carmichael
        - [Deep Learning] (http://www.deeplearningbook.org) by Begnio, Goodfellow and Courtville
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
