This chapter covers different frameworks using Explainable Artificial Intelligence (XAI) Python libraries to control biasness, execute the principles of reliability, and maintain ethics while generating predictions. As digitalization progresses touch different industries, they open up a whole new set of opportunities for the application of artificial intelligence and machine learning-related solutions. The major challenges with the adoption of these AI technologies ...
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022
P. MishraPractical Explainable AI Using Pythonhttps://doi.org/10.1007/978-1-4842-7158-2_22. AI Ethics, Biasness, and Reliability
Pradeepta Mishra1
(1)
Sobha Silicon Oasis, Bangalore, Karnataka, India
Get Practical Explainable AI Using Python: Artificial Intelligence Model Explanations Using Python-based Libraries, Extensions, and Frameworks now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
