Interpretable machine learning with Python : build explainable, fair, and robust high-performance models with hands-on, real-world examples / Serg Masis.

By:

Masis, Serg [author.]

Material type:

TextPublication details: Mumbai : Packt Publishing, 2022.Edition: 2nd edDescription: xxvii, 576 p. : 24 cmISBN:

9781803235424 (pbk.)

Subject(s):

DDC classification:

006.3 SER

Summary: A practical guide to interpreting machine learning models using Python, covering model-agnostic and model-specific interpretation methods, feature importance, SHAP, LIME, bias mitigation, causal inference, and techniques for making models more robust, fair, and reliable.

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Books	Central Library General stacks		Non-fiction		006.3 SER (Browse shelf(Opens below))					Checked out		27/09/2028	233593

Includes Index.

A practical guide to interpreting machine learning models using Python, covering model-agnostic and model-specific interpretation methods, feature importance, SHAP, LIME, bias mitigation, causal inference, and techniques for making models more robust, fair, and reliable.

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