context.py

doc_markdown = """
## What are adversarial examples? 💡

👉🏽 Do you think it is impossible to fool the vision system of a self-driving Tesla car?

👉🏽 Or that machine learning models used in malware detection software are too good to be evaded by hackers?

👉🏽 Or that face recognition systems in airports are bulletproof?

Like any of us machine learning enthusiasts, you might fall into the trap of thinking that deep models used out there are perfect.

### Well, you are WRONG.

There are easy ways to build **adversarial examples** that can fool any deep learning model and create security issues.

With this app you can create your own adversarial examples, using the **Iterative Fast Gradient Sign Method**, and fool [`Inception-v3`](https://en.wikipedia.org/wiki/Inceptionv3)


"""

st.markdown(doc_markdown)