Reproducible research and explaining predictions of any classifier

Recently I had a pleasure to give two talks at PyData Wrocław meetup group - about reproducible data science and explaining predictions of any classifier using LIME project. The meeting is taking place each month enabling others to discuss potential issues they encounter in their projects or simply share knowledge.


 

Reproducible data science

Practical approach

Assuring reproducibility is one of the most important issues in any scientific projects. See what techniques and tools you can use in your daily basis

Why have you done this to me?

Explaining predictions of any classifier

Very often it's nearly impossible to explain the decision made by a black-box classifier. But there is a new open source library solving this problem (LIME). Learn what's possible by seeing it in action.

Video

You can watch the whole presentation below (28:12):

You can download notebook and data files used in the examples here.

 

Norbert

Let's combine software craftsmanship and data engineering skills results to produce some clean and understandable code.