Linking pages
- The Road to Artificial Intelligence: An Ethical Minefield https://www.infoq.com/articles/algorithmic-integrity-ethics/ 1 comment
- GitHub - jphall663/awesome-machine-learning-interpretability: A curated list of awesome machine learning interpretability resources. https://github.com/jphall663/awesome-machine-learning-interpretability 0 comments
- GitHub - EthicalML/awesome-production-machine-learning: A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning https://github.com/EthicalML/awesome-production-machine-learning 0 comments
- GitHub - csinva/imodels: Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible). https://github.com/csinva/imodels 0 comments
- GitHub - r0f1/datascience: Curated list of Python resources for data science. https://github.com/r0f1/datascience 0 comments
- GitHub - ml-tooling/best-of-ml-python: 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly. https://github.com/ml-tooling/best-of-ml-python 0 comments
- GitHub - csinva/imodels: Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible). https://github.com/csinva/interpretability-implementations-demos 0 comments
- GitHub - interpretml/ebm2onnx: A tool to convert EBM models to ONNX https://github.com/SoftAtHome/ebm2onnx 0 comments
- GitHub - kelvins/awesome-mlops: A curated list of awesome MLOps tools https://github.com/kelvins/awesome-mlops 0 comments
- Microsoft debuts WhiteNoise, an AI toolkit for differential privacy | VentureBeat https://venturebeat.com/2020/05/19/microsoft-debuts-whitenoise-an-ai-toolkit-for-differential-privacy/ 0 comments
- Machine Learning Toolbox https://amitness.com/toolbox/ 0 comments
- GitHub - xiaohk/stickyland: Break the linear presentation of Jupyter Notebooks with sticky cells! https://github.com/xiaohk/stickyland 0 comments
- A brief Overview of some Ethical-AI Toolkits | by Murat Durmus (CEO @AISOMA_AG) | Nerd For Tech | Medium https://medium.com/nerd-for-tech/an-brief-overview-of-some-ethical-ai-toolkits-712afe9f3b3a 0 comments
- GitHub - RichardScottOZ/mineral-exploration-machine-learning: List of resources for mineral exploration and machine learning, generally with useful code and examples. https://github.com/RichardScottOZ/mineral-exploration-machine-learning 0 comments
Linked pages
- Plotly: Low-Code Data App Development https://plot.ly 48 comments
- GitHub - slundberg/shap: A game theoretic approach to explain the output of any machine learning model. https://github.com/slundberg/shap 20 comments
- Joblib: running Python functions as pipeline jobs — joblib 1.3.0.dev0 documentation https://joblib.readthedocs.io/en/latest/ 15 comments
- GitHub - marcotcr/lime: Lime: Explaining the predictions of any machine learning classifier https://github.com/marcotcr/lime 12 comments
- [1602.04938] "Why Should I Trust You?": Explaining the Predictions of Any Classifier http://arxiv.org/abs/1602.04938 1 comment
- [2204.09123] GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints https://arxiv.org/abs/2204.09123 1 comment
- GitHub - plotly/dash: Data Apps & Dashboards for Python. No JavaScript Required. https://github.com/plotly/dash 0 comments
- GitHub - pytest-dev/pytest: The pytest framework makes it easy to write small tests, yet scales to support complex functional testing https://github.com/pytest-dev/pytest 0 comments
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