DiCE
phoenix-chat-example
| DiCE | phoenix-chat-example | |
|---|---|---|
| 2 | 1 | |
| 1,276 | 732 | |
| 1.4% | 0.8% | |
| 8.2 | 7.7 | |
| 18 days ago | 15 days ago | |
| Python | Elixir | |
| MIT License | DHARMA |
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DiCE
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[D] Have researchers given up on traditional machine learning methods?
- all domains requiring high interpretability absolutely ignore deep learning at all, and put all their research into traditional ML; see e.g. counterfactual examples, important interpretability methods in finance, or rule-based learning, important in medical or law applications
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[R] The Shapley Value in Machine Learning
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.
phoenix-chat-example
What are some alternatives?
OmniXAI - OmniXAI: A Library for eXplainable AI
changelog.com - Changelog is news and podcast for developers. This is our open source platform.
CARLA - CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
magnetissimo - Web application that indexes all popular torrent sites, and saves it to the local database.
AIX360 - Interpretability and explainability of data and machine learning models
elixir_koans - Elixir learning exercises
interpret - Fit interpretable models. Explain blackbox machine learning.
phoenix-liveview-counter-tutorial - 🤯 beginners tutorial building a real time counter in Phoenix 1.7.7 + LiveView 0.19 ⚡️ Learn the fundamentals from first principals so you can make something amazing! 🚀
harakiri - Help applications kill themselves
tilex - Today I Learned
stranger - Chat anonymously with a randomly chosen stranger
dice - Roll the dice, in elixir