Interpretable Machine Learning with Python

Table of Contents

Interpretation, Interpretability and Explainability; and why does it all matter?
Key Concepts of Interpretability
Interpretation Challenges
Fundamentals of Feature Importance and Impact
Global Model-Agnostic Interpretation Methods
Local Model-Agnostic Interpretation Methods
Anchor and Counterfactual Explanations
Visualizing Convolutional Neural Networks
Interpretation Methods for Multivariate Forecasting and Sensitivity Analysis
Feature Selection and Engineering for Interpretability
Bias Mitigation and Causal Inference Methods
Monotonic Constraints and Model Tuning for Interpretability
Adversarial Robustness
What's Next for Machine Learning Interpretability?

Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.

• Os sistemas especialistas / sistemas baseados em conhecimento
• Aprendizagem mecânica
• Modelagem computacional e simulação
• As redes neurais e sistemas nebulosos

hands-on machine learning; machine learning python; ai/ml; machine learning book; hands on machine learning; ai and machine learning; ml with python