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152 public repositories
matching this topic...
Fit interpretable models. Explain blackbox machine learning.
Debugging, monitoring and visualization for Python Machine Learning and Data Science
Updated
May 15, 2020
Jupyter Notebook
Machine Learning in one line of code
Updated
Jul 31, 2020
Python
Updated
Jul 9, 2020
Python
moDel Agnostic Language for Exploration and eXplanation
Updated
Aug 3, 2020
Python
Interpretability and explainability of data and machine learning models
Updated
Jul 14, 2020
Python
Code, exercises and tutorials of my personal blog ! 📝
Updated
Feb 18, 2020
Jupyter Notebook
XAI - An eXplainability toolbox for machine learning
Updated
Oct 5, 2019
Python
Generate Diverse Counterfactual Explanations for any machine learning model.
Updated
Jul 7, 2020
Python
Leave One Feature Out Importance
Updated
Jul 2, 2020
Python
🕵️♂️ Interpreting Convolutional Neural Network (CNN) Results.
Updated
Mar 29, 2019
Jupyter Notebook
📍 Interactive Studio for Explanatory Model Analysis
A repository for explaining feature attributions and feature interactions in deep neural networks.
Updated
May 1, 2020
Jupyter Notebook
Using / reproducing ACD (ICLR 2019) from the paper "Hierarchical interpretations for neural network predictions"
Updated
Jul 23, 2020
Jupyter Notebook
Pytorch implementation of "Explainable and Explicit Visual Reasoning over Scene Graphs "
Updated
Mar 17, 2019
Python
💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow)
Updated
Aug 1, 2020
Python
Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
Updated
Jan 27, 2020
Python
Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge"
https://arxiv.org/abs/1909.13584
Updated
Jul 23, 2020
Jupyter Notebook
A fast Tsetlin Machine implementation employing bit-wise operators, with MNIST demo.
Explain any Black-Box Machine Learning Model with explainX: Fast, Scalable & State-of-the-art Explainable AI Platform.
Updated
Jul 23, 2020
Jupyter Notebook
Updated
Jul 2, 2020
Jupyter Notebook
[CVPR 2020 Oral] Interpretable and Accurate Fine-grained Recognition via Region Grouping
Updated
Jul 8, 2020
Python
Workshop: Explanation and exploration of machine learning models with R and DALEX at eRum 2020
Explaining the output of machine learning models with more accurately estimated Shapley values
Updated
Apr 15, 2019
Python
code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018
Updated
Feb 7, 2019
Jupyter Notebook
Fast approximate Shapley values in R
Essential NLP & ML, short & fast pure Python code
Updated
Jun 22, 2020
Python
All about explainable AI, algorithmic fairness and more
Modular Python Toolbox for Fairness, Accountability and Transparency Forensics
Updated
Jul 9, 2020
Python
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