Applied machine learning explainability techniques : best practices for making ML algorithms interpretable in the real-world applications using LIME, SHAP and others /: best practices for making ML algorithms interpretable in the real-world applications using LIME, SHAP and others. (2022)

Record Type:
Book
Title:
Applied machine learning explainability techniques : best practices for making ML algorithms interpretable in the real-world applications using LIME, SHAP and others /: best practices for making ML algorithms interpretable in the real-world applications using LIME, SHAP and others. (2022)
Main Title:
Applied machine learning explainability techniques : best practices for making ML algorithms interpretable in the real-world applications using LIME, SHAP and others
Further Information:
Note: Aditya Bhattacharya.
Authors:
Bhattacharya, Aditya
Publisher Details:
Birmingham : Packt Publishing
Publication Date:
2022
Extent:
1 online resource
Subjects:
006.31
Machine learning
Languages:
English
ISBNs:
9781803234168
Related ISBNs:
9781803246154
Notes:
Note: Description based on CIP data; resource not viewed.
Access Rights:
Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
Access Usage:
Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
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Physical Locations:
British Library HMNTS - ELD.DS.705849
Ingest File:
13_026.xml