Model interpretability is an area that needs special attention because it is connected with model adoption in particular and AI adoption in general. Users will adopt a model and framework if they can explain the decisions or predictions generated by the deep learning model. In this chapter, you will explore a new framework called Captum, which consists of a set of algorithms that can explain or help us interpret the predictions, model results, and layers of a neural network model. ...
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2023
P. MishraPyTorch Recipeshttps://doi.org/10.1007/978-1-4842-8925-9_1010. PyTorch Model Interpretability and Interface to Sklearn
Pradeepta Mishra1
(1)
Bangalore, Karnataka, India
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