Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python

Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python

Mishra, Pradeepta

Paperback

General ComputersProgramming

Publisher Price: $37.99

ISBN10: 1484290283
ISBN13: 9781484290286
Publisher: Apress
Published: Feb 9 2023
Pages: 254
Weight: 0.87
Height: 0.59 Width: 6.14 Depth: 9.21
Language: English
Understand how to use Explainable AI (XAI) libraries and build trust in AI and machine learning models. This book utilizes a problem-solution approach to explaining machine learning models and their algorithms.
The book starts with model interpretation for supervised learning linear models, which includes feature importance, partial dependency analysis, and influential data point analysis for both classification and regression models. Next, it explains supervised learning using non-linear models and state-of-the-art frameworks such as SHAP values/scores and LIME for local interpretation. Explainability for time series models is covered using LIME and SHAP, as are natural language processing-related tasks such as text classification, and sentiment analysis with ELI5, and ALIBI. The book concludes with complex model classification and regression-like neural networks and deep learning models using the CAPTUM framework that shows feature attribution, neuron attribution, and activation attribution.

Also from

Mishra, Pradeepta

View All

Also in

General Computers

View All