Implementation of these techniques on different models
Last updated
Last updated
In this section, we will show how to do the implementation of the Interpretability techniques explained until now. These techniques will be applied to different Machine Learning models.
Each model is interpreted using a different technique.
Each implementation will have a Google co-laboratory linked to it. Every co-laboratory notebook has model interpretability demostration with different datasets. We encourage everyone to go there and run the notebooks to see how interpretability can be achieved with Python code.
You can even download the notebooks and play around with them in your local system.
To know more about the Google co-laboratory refer the link.