Metadata-Version: 2.1
Name: WestCoastAD
Version: 1.0
Summary: An Optimization Package with an Automatic Differenation Core
Home-page: https://github.com/West-Coast-Differentiators/cs107-FinalProject
Author: Anita Mahinpei, Yingchen Liu, Erik Adames, Lekshmi Santhosh
License: UNKNOWN
Description: [![codecov](https://codecov.io/gh/West-Coast-Differentiators/cs107-FinalProject/branch/master/graph/badge.svg?token=CVUJ0SI09S)](https://codecov.io/gh/West-Coast-Differentiators/cs107-FinalProject)
        [![Build Status](https://travis-ci.com/West-Coast-Differentiators/cs107-FinalProject.svg?token=LcEGi8DXzVyEeNU9JqUx&branch=master)](https://travis-ci.com/West-Coast-Differentiators/cs107-FinalProject)
        
        # cs107-FinalProject
        
        ## Group 14
        * Anita Mahinpei
        * Yingchen Liu
        * Erik Adames
        * Lekshmi Santhosh
        
        
        # Project description
        
        Our package contains several optimization algorithms that are ubiquitous in machine learning. In the context of the WestCoastAD package, an optimization problem refers to the minimization of a function. Below are the optimization that are currently included in this package:
          * Gradient Descent
          * Momentum Gradient Descent
          * AdaGrad
          * RMSprop
          * Adam
          * BFGS
        
        All the optimization methods mentioned above require derivative computations. For this library, we have used Automatic Differentiation as it is an efficient way of computing these derivatives which can be used with various complex functions.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
