Python explainable-ai

Open-source Python projects categorized as explainable-ai Edit details

Top 10 Python explainable-ai Projects

  • MindsDB

    In-Database Machine Learning

    Project mention: MindsDB Integration with Supabase | reddit.com/r/opensource | 2022-06-17

    I am attending this contest and I would like to share with you my proposal for the MindsDB ideation challenge. https://github.com/mindsdb/mindsdb/issues/2315

  • AIX360

    Interpretability and explainability of data and machine learning models

    Project mention: [R] Explaining the Explainable AI: A 2-Stage Approach - Link to a free online lecture by the author in comments | reddit.com/r/MachineLearning | 2022-03-20

    One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques https://arxiv.org/abs/1909.03012 https://github.com/Trusted-AI/AIX360

  • JetBrains

    Developer Ecosystem Survey 2022. Take part in the Developer Ecosystem Survey 2022 by JetBrains and get a chance to win a Macbook, a Nvidia graphics card, or other prizes. We’ll create an infographic full of stats, and you’ll get personalized results so you can compare yourself with other developers.

  • DALEX

    moDel Agnostic Language for Exploration and eXplanation

    Project mention: Twitter set to accept ‘best and final offer’ of Elon Musk | reddit.com/r/news | 2022-04-25

    Which he will not do, because: a) He can't, it's a black box algorithm. It actually is open source already, but that doesn't mean much as it's useless without Twitter's data https://github.com/ModelOriented/DALEX b) He won't release data that shows the algorithm is racist and amplifies conservative and extremist content. He won't remove such functions because it will cost him billions.

  • DiCE

    Generate Diverse Counterfactual Explanations for any machine learning model. (by interpretml)

    Project mention: [R] The Shapley Value in Machine Learning | reddit.com/r/MachineLearning | 2022-02-25

    Counter-factual and recourse-based explanations are alternative approach to model explanations. I used to work in a large financial institution, and we were researching whether counter-factual explanation methods would lead to better reason codes for adverse action notices.

  • vit-explain

    Explainability for Vision Transformers

    Project mention: Explainability for Vision Transformers TF Implementation | reddit.com/r/learnmachinelearning | 2022-04-21

    Im trying to implement this code of visualization/explainability of ViT's in tensorflow but im having trouble trying to find a similar function of the module.RegisterForwardHook for TF. Any ideas on how can I do it?

  • CARLA

    CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms (by carla-recourse)

    Project mention: [R] CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms | reddit.com/r/MachineLearning | 2021-09-29

    Abstract: Counterfactual explanations provide means for prescriptive model explanations by suggesting actionable feature changes (e.g., increase income) that allow individuals to achieve favourable outcomes in the future (e.g., insurance approval). Choosing an appropriate method is a crucial aspect for meaningful counterfactual explanations. As documented in recent reviews, there exists a quickly growing literature with available methods. Yet, in the absence of widely available open–source implementations, the decision in favour of certain models is primarily based on what is readily available. Going forward – to guarantee meaningful comparisons across explanation methods – we present CARLA (Counterfactual And Recourse Library), a python library for benchmarking counterfactual explanation methods across both different data sets and different machine learning models. In summary, our work provides the following contributions: (i) an extensive benchmark of 11 popular counterfactual explanation methods, (ii) a benchmarking framework for research on future counterfactual explanation methods, and (iii) a standardized set of integrated evaluation measures and data sets for transparent and extensive comparisons of these methods. We have open sourced CARLA and our experimental results on GitHub, making them available as competitive baselines. We welcome contributions from other research groups and practitioners.

  • explainable-cnn

    📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.

    Project mention: PyTorch based explainable-cnn | reddit.com/r/deeplearning | 2022-03-28
  • SonarLint

    Deliver Cleaner and Safer Code - Right in Your IDE of Choice!. SonarLint is a free and open source IDE extension that identifies and catches bugs and vulnerabilities as you code, directly in the IDE. Install from your favorite IDE marketplace today.

  • shapley

    The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).

    Project mention: AstraZeneca Researchers Explain the Concept and Applications of the Shapley Value in Machine Learning | reddit.com/r/artificial | 2022-02-17

    Code for https://arxiv.org/abs/2202.05594 found: https://github.com/benedekrozemberczki/shapley

  • sagemaker-explaining-credit-decisions

    Amazon SageMaker Solution for explaining credit decisions.

    Project mention: Deploying a LightGBM classifier as a AWS Sagemaker endpoint? | reddit.com/r/mlops | 2021-08-25

    Have looked at: https://sagemaker-examples.readthedocs.io/en/latest/advanced_functionality/scikit_bring_your_own/scikit_bring_your_own.html https://docs.aws.amazon.com/sagemaker/latest/dg/docker-containers-create.html https://sagemaker-immersionday.workshop.aws/lab3/option1.html The above don't specify LightGBM, but the concept of Bring Your Own Container/Algorithm is the same. I think this article might be more than what you need, buy it does reference LightGBM https://github.com/awslabs/sagemaker-explaining-credit-decisions And also this one https://github.com/aws-samples/amazon-sagemaker-script-mode/blob/master/lightgbm-byo/lightgbm-byo.ipynb

  • neuro-symbolic-sudoku-solver

    ⚙️ Solving sudoku using Deep Reinforcement learning in combination with powerful symbolic representations.

    Project mention: Neuro-Symbolic Sudoku Solver | reddit.com/r/Python | 2021-12-02

    Github: https://github.com/ashutosh1919/neuro-symbolic-sudoku-solver

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2022-06-17.

Python explainable-ai related posts

Index

What are some of the best open-source explainable-ai projects in Python? This list will help you:

Project Stars
1 MindsDB 8,022
2 AIX360 1,123
3 DALEX 1,061
4 DiCE 861
5 vit-explain 335
6 CARLA 169
7 explainable-cnn 167
8 shapley 165
9 sagemaker-explaining-credit-decisions 79
10 neuro-symbolic-sudoku-solver 54
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