interpretml / interpret

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Interpret

wh3nd1g0h commented Jul 29, 2020

Yes

jphall663 / awesome-machine-learning-interpretability

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A curated list of awesome machine learning interpretability resources.

python data-science machine-learning data-mining awesome r awesome-list transparency fairness accountability interpretability interpretable-deep-learning interpretable-ai interpretable-ml explainable-ml xai fatml interpretable-machine-learning iml machine-learning-interpretability

Updated Aug 20, 2020

lopusz / awesome-interpretable-machine-learning

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data-science machine-learning interpretable-ai interpretable-ml explainable-ai xai interpretable-machine-learning

Updated Jul 9, 2020
Python

ModelOriented / DALEX

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moDel Agnostic Language for Exploration and eXplanation

black-box data-science machine-learning predictive-modeling interpretability explainable-artificial-intelligence explanations explainable-ai explainable-ml xai model-visualization interpretable-machine-learning iml dalex explanatory-model-analysis

Updated Aug 20, 2020
Python

dswah / pyGAM

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add example for empirical prediction intervals using sampling

1

dswah commented Feb 21, 2018

using the approach laid out in:
dswah/pyGAM#154

add tolerance intervals

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add negative binomial and correspong log link

10

Find more good first issues →

jphall663 / interpretable_machine_learning_with_python

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Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

python data-science machine-learning data-mining h2o gradient-boosting-machine transparency decision-tree fairness lime accountability interpretability interpretable-ai interpretable-ml xai fatml interpretable interpretable-machine-learning iml machine-learning-interpretability

Updated Aug 11, 2020
Jupyter Notebook

pbiecek / xai_resources

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Interesting resources related to XAI (Explainable Artificial Intelligence)

interpretability xai interpretable-machine-learning

Updated Jul 5, 2020
R

h2oai / mli-resources

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H2O.ai Machine Learning Interpretability Resources

python data-science machine-learning data-mining h2o xgboost transparency jupyter-notebooks fairness accountability interpretability interpretable-ai interpretable-ml explainable-ml mli xai fatml interpretable-machine-learning iml machine-learning-interpretability

Updated May 22, 2020
Jupyter Notebook

interpretml / DiCE

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Generate Diverse Counterfactual Explanations for any machine learning model.

machine-learning deep-learning explainable-ai explainable-ml xai interpretable-machine-learning counterfactual-explanations

Updated Aug 18, 2020
Python

idealo / cnn-exposed

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🕵️‍♂️ Interpreting Convolutional Neural Network (CNN) Results.

machine-learning computer-vision deep-learning neural-network explainable-ai interpretable-machine-learning

Updated Mar 29, 2019
Jupyter Notebook

sergioburdisso / pyss3

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A Python package implementing a new model for text classification with visualization tools for Explainable AI

nlp machine-learning natural-language-processing text-mining data-mining text-classification machine-learning-algorithms artificial-intelligence document-classification sentence-classification interpretability multilabel-classification explainable-artificial-intelligence interpretable-ml xai interpretable-machine-learning document-categorization early-classification text-labeling ss3-classifier

Updated Aug 19, 2020
Python

ModelOriented / modelStudio

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📍 Interactive Studio for Explanatory Model Analysis

machine-learning predictive-modeling interactive-visualizations interpretability explainable-artificial-intelligence explainable-ai explainable-ml xai model-visualization interpretable-machine-learning iml explainability explanatory-model-analysis explainable-machine-learning

Updated Aug 17, 2020
R

atulshanbhag / Layerwise-Relevance-Propagation

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Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers

visualization deep-learning interpretable-deep-learning interpretable-machine-learning

Updated Aug 21, 2018
Python

explainX / explainx

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ExplainX is a fast, light-weight, and scalable explainable AI framework for data scientists to explain and debug any black-box model.

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Updated Aug 19, 2020
Jupyter Notebook

jrieke / cnn-interpretability

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🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease

machine-learning deep-learning cnn mri medical-imaging convolutional-neural-networks alzheimers-disease interpretability alzheimer-disease-prediction interpretable-machine-learning visualization-methods

Updated Jul 5, 2019
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pbiecek / XAIatERUM2020

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Workshop: Explanation and exploration of machine learning models with R and DALEX at eRum 2020

explainable-ai interpretable-machine-learning dalex explanatory-model-analysis

Updated Jun 20, 2020
R

firmai / ml-fairness-framework

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FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)

contrastive counterfactual explainable-ai explainable-ml xai interpretable-machine-learning fairness-ai aif360 fairness-ml alibi prototypical aix360 fairness-indicators

Updated Jun 5, 2020
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bgreenwell / fastshap

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Fast approximate Shapley values in R

variable-importance explainable-ai explainable-ml xai shapley interpretable-machine-learning shapley-values

Updated Feb 2, 2020
R

andreysharapov / xaience

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All about explainable AI, algorithmic fairness and more

interpretability explainable-artificial-intelligence interpretable-deep-learning interpretable-ai explainable-ai explainable-ml interpretable-machine-learning

Updated Jul 20, 2020

cair / convolutional-tsetlin-machine-tutorial

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Tutorial on the Convolutional Tsetlin Machine

convolution pattern-recognition propositional-logic bandit-learning frequent-pattern-mining rule-based interpretable-machine-learning tsetlin-machine

Updated Mar 26, 2020
Python

sayakpaul / Benchmarking-and-MLI-experiments-on-the-Adult-dataset

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Contains benchmarking and interpretability experiments on the Adult dataset using several libraries

data-science machine-learning tensorflow fastai h2oai interpretable-machine-learning microsoft-interpret

Updated May 19, 2019
Jupyter Notebook

BioroboticsLab / IBA

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Information Bottlenecks for Attribution

deep-learning explainable-ai interpretable-machine-learning

Updated May 31, 2020
Python

svarthafnyra / CNN_Visualizations

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Visualization of Adversarial Examples

visualization convolutional-networks interpretable-machine-learning attack-types

Updated Oct 14, 2018
Python

cair / pyTsetlinMachineParallel

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Multi-threaded implementation of the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features and multigranularity.

machine-learning regression classification convolution propositional-logic bandit-learning frequent-pattern-mining rule-based interpretable-machine-learning tsetlin-machine

Updated Jul 7, 2020
C

keiserlab / plaquebox-paper

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Repo for Tang et al, bioRxiv 454793 (2018)

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Updated Mar 24, 2019
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jphall663 / diabetes_use_case

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Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/

python data-science machine-learning data-mining healthcare xgboost transparency interpretability interpretable-ml explainable-ml xai interpretable-machine-learning iml machine-learning-interpretability

Updated Sep 7, 2018
Jupyter Notebook

SinaMohseni / Awesome-XAI-Evaluation

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Reference tables to introduce and organize evaluation methods and measures for explainable machine learning systems

awesome awesome-list interpretable-machine-learning xai-evaluation

Updated May 4, 2020

rehmanzafar / xai-iml-sota

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Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.

machine-learning human-in-the-loop interpretability explainable-artificial-intelligence researchers interactive-machine-learning deep-learning-visualization human-in-the-loop-machine-learning explainable-ml xai interpretable interpretable-machine-learning iml model-interpretability explainable interpretable-models explainable-models interpretable-learning explaining-ai explanation-methods

Updated Aug 18, 2020
R

nredell / ShapML.jl

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A Julia package for interpretable machine learning with stochastic Shapley values

julia feature-importance shapley interpretable-machine-learning iml shap shapley-value stochastic-shapley-values

Updated Jul 10, 2020
Julia

jphall663 / hc_ml

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Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.

data-science machine-learning data-mining transparency fairness accountability interpretability interpretable-ai interpretable-ml explainable-ai explainable-ml xai fatml interpretable-machine-learning iml machine-learning-interpretability fairness-ai fairness-ml

Updated Nov 19, 2019
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interpretable-machine-learning

Here are 87 public repositories matching this topic...

interpretml / interpret

Interpret

jphall663 / awesome-machine-learning-interpretability

lopusz / awesome-interpretable-machine-learning

ModelOriented / DALEX

dswah / pyGAM

add example for empirical prediction intervals using sampling

add tolerance intervals

add negative binomial and correspong log link

jphall663 / interpretable_machine_learning_with_python

pbiecek / xai_resources

h2oai / mli-resources

interpretml / DiCE

idealo / cnn-exposed

sergioburdisso / pyss3

ModelOriented / modelStudio

atulshanbhag / Layerwise-Relevance-Propagation

explainX / explainx

jrieke / cnn-interpretability

pbiecek / XAIatERUM2020

firmai / ml-fairness-framework

bgreenwell / fastshap

andreysharapov / xaience

cair / convolutional-tsetlin-machine-tutorial

sayakpaul / Benchmarking-and-MLI-experiments-on-the-Adult-dataset

BioroboticsLab / IBA

svarthafnyra / CNN_Visualizations

cair / pyTsetlinMachineParallel

keiserlab / plaquebox-paper

jphall663 / diabetes_use_case

SinaMohseni / Awesome-XAI-Evaluation

rehmanzafar / xai-iml-sota

nredell / ShapML.jl

jphall663 / hc_ml

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