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an automatic differentiation package created by AC207 students

Project description

team21

Continuous Integration Test Coverage for Milestone 2 test AD for Milestone 2

Brief Introduction

funAD is a PyPi-distributed package that executes forward-mode of automatic differentiation, enabling users to solve functional derivatives with high computational efficiency and machine precision.

This project/package is the fruit of Harvard CS107/AC207 class final project in 2022 Fall. Our package utilize forward mode and dual number. Additionally, we also allow users to define their own seeds vector for the Jacobian Matrix and the option to calculate local maxima and minima through gradient descent.

To install, run the following command in your terminal

pip install funAD

For details instruction on how to use this package, please follow the steps in the usage page.

Group Number:

Group 21

Group Members:

Zhecheng Yao zhechengyao@g.harvard.edu

Hanlin Zhu hzhu@g.harvard.edu

Xu Tang xutang@g.harvard.edu

Tiantong Li tiantongli@g.harvard.edu

Harvard University, Fall 2022

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