semvec/pypi-packages huggingface dataset:
AdversarialFriend 1.0
Group Project for CS 5523
License: MIT
Requires Python: >=3.6

# CS_5523_Final_Project

**This repo contains code and files of final project in CS 5523 Data Minning** 

## Team Members 

Yangyang Li <li002252@umn.edu>

Jacob <isle0011@umn.edu>   

Mario <serra082@umn.edu>

## Project Description 

We begin this report by re-stating the purpose of our project for the necessary context. Then, we give an overview of the progress made so far, and go on to describe in greater detail each of the project components that we've implemented. Finally, We close this report by discussing the challenges we've encountered, as well as the next steps in our plan and our (very slightly) re-aligned vision for the final submission.


## TODO 

1. **Visualize Logistic Regression, Adversarial Method**

2. **Visualize Activation Maps/Kernels in CNNs**

3. **Class Activation Maps**

4. **Produce Adversarial Examples**


## Reference 


[1] C. Olah, A. Satyanarayan, I, Johnson, S. Carter, L. Schubert, K. Ye, A. Mordvinstev, “The Building Blocks of Interpretability” Distill, 6-Mar-2018. [Online](https://distill.pub/2018/building-blocks/) [Accessed: 1-Dec-2020]

[2] J. Johnson, EECS 498-007 / 598-005 Deep Learning for Computer Vision, University of Michigan, 10-Aug-2020. [Online](https://www.youtube.com/watch?v=qcSEP17uKKY&t=823s) [Accessed: 1-Dec-2020]

[3]  A. Kurakin, I. Goodfellow, S. Bengio, “Adversarial Examples in the Physical World” ICLR, 8-Jul-2016. [Online](https://arxiv.org/pdf/1607.02533.pdf) [Accessed: 1-Dec-2020]