Practical explainable AI using Python artificial intelligence model explanations using Python-based libraries, extensions, and frameworks /
Learn the ins and outs of decisions, biases, and reliability of AI algorithms and how to make sense of these predictions. This book explores the so-called black-box models to boost the adaptability, interpretability, and explainability of the decisions made by AI algorithms using frameworks such as...
| Main Author: | Mishra, Pradeepta. |
|---|---|
| Other Authors: | SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Berkeley, CA :
Apress L.P.,
2022.
Berkeley, CA : 2022. |
| Physical Description: |
1 online resource (356 pages) |
| Subjects: |
CMU Electronic Access
Electronic Resource Click Here| Location | Call Number: | Status |
|---|---|---|
| CMU Electronic Access | Available |