Hacker News
- Lime: Explaining the predictions of any machine learning classifier https://github.com/marcotcr/lime 9 comments
- Lime: model agnostic interpretability for machine learning https://github.com/marcotcr/lime 2 comments
Linking pages
- How to solve 90% of NLP problems: a step-by-step guide | by Emmanuel Ameisen | Insight https://blog.insightdatascience.com/how-to-solve-90-of-nlp-problems-a-step-by-step-guide-fda605278e4e 74 comments
- GitHub - josephmisiti/awesome-machine-learning: A curated list of awesome Machine Learning frameworks, libraries and software. https://github.com/josephmisiti/awesome-machine-learning 58 comments
- GitHub - microsoft/tensorwatch: Debugging, monitoring and visualization for Python Machine Learning and Data Science https://github.com/microsoft/tensorwatch 12 comments
- The best open source software of 2021 | InfoWorld https://www.infoworld.com/article/3637038/the-best-open-source-software-of-2021.html 5 comments
- TOP-39 most popular JS repositories in February 2018 | by Iren Korkishko | ITNEXT https://medium.com/@iren.korkishko/top-40-most-popular-js-repositories-in-february-2018-72a047c3c047 5 comments
- GitHub - xplainable/xplainable: Real-time explainable machine learning for business optimisation https://github.com/xplainable/xplainable 4 comments
- GitHub - prakhar21/50-Days-of-ML: A day to day plan for this challenge (50 Days of Machine Learning) . Covers both theoretical and practical aspects https://github.com/prakhar21/100-Days-of-ML 3 comments
- Performance metrics aren't everything http://tommyblanchard.com/performance-metrics-arent-everything 3 comments
- GitHub - Mybridge/amazing-machine-learning-opensource-2019: Amazing Machine Learning Open Source Tools and Projects for the Past Year (v.2019) https://github.com/Mybridge/amazing-machine-learning-opensource-2019 3 comments
- Going beyond simple error analysis of ML systems https://alexandruburlacu.github.io/posts/2021-07-26-ml-error-analysis 2 comments
- Deep Learning vs. Machine Learning: What Are the Differences? | Apriorit https://www.apriorit.com/dev-blog/472-machine-learning-applications 1 comment
- What we talk about when we talk about fair AI | by Fionntán O’Donnell | BBC News Labs | Medium https://medium.com/bbc-news-labs/what-we-talk-about-when-we-talk-about-fair-ai-8c72204f0798 1 comment
- Q1 & Q2, 2024 Update: A Comprehensive Guide for GenAI Safety and Security https://securedgenai.substack.com/p/q1-and-q2-2024-update-a-comprehensive 1 comment
- How to build TRUST in Machine Learning, the sane way | by Eyal Trabelsi | Bigabid’s Brain | Medium https://medium.com/bigabids-dataverse/how-to-build-trust-in-machine-learning-the-sane-way-39d879f22e69 0 comments
- 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
- Feature importance — what’s in a name? | by Sven Stringer | bigdatarepublic | Medium https://medium.com/bigdatarepublic/feature-importance-whats-in-a-name-79532e59eea3 0 comments
- How to Mitigate Bias in AI Systems | Toptal https://www.toptal.com/artificial-intelligence/mitigating-ai-bias 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 - r0f1/datascience: Curated list of Python resources for data science. https://github.com/r0f1/datascience 0 comments
- Interpretable Machine Learning with Python - Savvas Tjortjoglou http://savvastjortjoglou.com/intrepretable-machine-learning-nfl-combine.html 0 comments
Linked pages
- [1602.04938] "Why Should I Trust You?": Explaining the Predictions of Any Classifier http://arxiv.org/abs/1602.04938 1 comment
- Local Interpretable Model-Agnostic Explanations (LIME): An Introduction â OâReilly https://www.oreilly.com/learning/introduction-to-local-interpretable-model-agnostic-explanations-lime 0 comments
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