# Postscript: Real world applications of classic machine learning

In this section of the curriculum, you will be introduced to some real-world applications of classical ML. We have scoured the internet to find whitepapers and articles about applications that have used these strategies, avoiding neural networks, deep learning and AI as much as possible. Learn about how ML is used in business systems, ecological applications, finance, arts and culture, and more.

![chess](images/chess.jpg)

> Photo by <a href="https://unsplash.com/@childeye?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Alexis Fauvet</a> on <a href="https://unsplash.com/s/photos/artificial-intelligence?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
  
## Lesson

1. [Real-World Applications for ML](1-Applications/README.md)
2. [Model Debugging in Machine Learning using Responsible AI dashboard components](2-Debugging-ML-Models/README.md)

## Credits

"Real-World Applications" was written by a team of folks, including [Jen Looper](https://twitter.com/jenlooper) and [Ornella Altunyan](https://twitter.com/ornelladotcom).

"Model Debugging in Machine Learning using Responsible AI dashboard components" was written by [Ruth Yakubu](https://twitter.com/ruthieyakubu)