interpretml / interpret

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Open

Interpret

4

wh3nd1g0h commented Jul 29, 2020

Yes

mindsdb / mindsdb

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Open

Update Install instructions on README.md

1

torrmal commented Oct 1, 2020

We want to suggest people to run mindsdb on a venv,
and we require python 3.8

Can you update the README.md so it reflects

create and activate venv:

  python3.9 -m venv venv
  source venv/bin/activate

install MindsDB:

  pip3 install mindsdb

Run MindsDB

    python3.8 -m mindsdb

check if python version < 3.8 on server start

3

Open

Change STDOUT on server start

8

Find more good first issues →

jphall663 / awesome-machine-learning-interpretability

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A curated list of awesome machine learning interpretability resources.

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SeldonIO / alibi

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Algorithms for monitoring and explaining machine learning models

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EthicalML / xai

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XAI - An eXplainability toolbox for machine learning

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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.

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Interesting resources related to XAI (Explainable Artificial Intelligence)

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h2oai / mli-resources

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H2O.ai Machine Learning Interpretability Resources

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interpretml / DiCE

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Generate Diverse Counterfactual Explanations for any machine learning model.

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sergioburdisso / pyss3

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

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Layer-wise Relevance Propagation (LRP) for LSTMs

recurrent-neural-networks interpretability xai lstms

Updated Apr 24, 2020
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ModelOriented / modelStudio

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📍 Interactive Studio for Explanatory Model Analysis

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Pytorch Implementation of recent visual attribution methods for model interpretability

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Explain & debug blackbox machine learning algorithms.

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Model Agnostics breakDown plots

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A curated list of awesome Fairness in AI resources

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Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)

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Detect model's attention

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oegedijk / explainerdashboard

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firmai / ml-fairness-framework

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

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Fast approximate Shapley values in R

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Updated Aug 25, 2020
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Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN

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Updated Aug 21, 2019
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Minimal starting point for rapid prototyping interactive Human-AI tools

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liznerski / fcdd

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Repository for the Explainable Deep One-Class Classification paper

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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/

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Here are 127 public repositories matching this topic...

interpretml / interpret

Interpret

mindsdb / mindsdb

Update Install instructions on README.md

check if python version < 3.8 on server start

Change STDOUT on server start

jphall663 / awesome-machine-learning-interpretability

SeldonIO / alibi

lopusz / awesome-interpretable-machine-learning

Trusted-AI / AIX360

ModelOriented / DALEX

EthicalML / xai

jphall663 / interpretable_machine_learning_with_python

pbiecek / xai_resources

h2oai / mli-resources

interpretml / DiCE

sergioburdisso / pyss3

ArrasL / LRP_for_LSTM

ModelOriented / modelStudio

yulongwang12 / visual-attribution

explainX / explainx

pbiecek / ema

pbiecek / breakDown

datamllab / awesome-fairness-in-ai

ModelOriented / iBreakDown

eclique / RISE

ModelOriented / auditor

oegedijk / explainerdashboard

firmai / ml-fairness-framework

bgreenwell / fastshap

ModelOriented / live

HendrikStrobelt / sentimenter_minimal_hai

liznerski / fcdd

jphall663 / diabetes_use_case

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