Interpretable Machine Learning Github
Listing Websites about Interpretable Machine Learning Github
interpretable-machine-learning · GitHub Topics · GitHub
(6 days ago) black-box data-science machine-learning predictive-modeling fairness interpretability explainable-artificial-intelligence explanations explainable-ai explainable-ml xai model-visualization interpretable-machine-learning iml dalex responsible-ai responsible-ml explanatory-model-analysis. Updated on Sep 13, 2021. Python.
Interpretable Machine Learning - GitHub Pages
(1 days ago) This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. The focus of the book is on model-agnostic methods for interpreting black box models such as
GitHub - tridungduong16/Interpretable-Machine-Learning
(4 days ago) Paper Link. model-agnostic approach for providing inter-pretable explanations for predictions of any GNN-based model on any graph-basedmachine learning task. GNNEXPLAINER as an optimization task that maximizes the mutual information between a GNN’s predic-tion and distribution of possible subgraph structures.
Interpretable Machine Learning with Python - GitHub
(7 days ago)
- What Is This Book About?
- Instructions and Navigations
- Get to Know The Authors
- Do you want to understand your models and mitigate the risks associated with poor predictions using practical machine learning (ML) interpretation? Interpretable Machine Learning with Python can help you overcome these challenges, using interpretation methods to build fairer and safer ML models. This book covers the following exciting features: 1.