Explainable AI Models in Python
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This book explores so-called “black box” models to improve the adaptability, interpretability, and explainability of decisions made by artificial intelligence (AI) algorithms, using frameworks such as the Python XAI, TensorFlow 2.0+, Keras, and custom libraries frameworks using Python wrappers. The fundamentals of model explainability and interpretability are outlined, and methods and systems for interpreting linear, nonlinear, and time series models used in AI are discussed. You will learn how an AI algorithm makes decisions and how to make an AI model interpretable and explainable, and become familiar with deep learning models.
FL/873916/R
Data sheet
- Name of the Author
- Прадипта Мишра
- Language
- Russian
- Translator
- С. В. Минц
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This book explores so-called “black box” models to improve the adaptability, interpretability, and explainability of decisions made by artificial intelligenc...