kennethleungty/Failed-ML
A compiled list of high-profile real-world machine learning project failures with explanations and case studies.
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This repository aggregates documented failures of ML systems across domains including computer vision, NLP, recommendation systems, and forecasting. Each case study describes what went wrong and the lessons learned, serving as a reference for ML practitioners to understand common pitfalls in production systems.
Frequently asked
- What is kennethleungty/Failed-ML?
- A compiled list of high-profile real-world machine learning project failures with explanations and case studies.
- Is Failed-ML open source?
- Yes — kennethleungty/Failed-ML is open source, released under the MIT license.
- How popular is Failed-ML?
- kennethleungty/Failed-ML has 753 stars on GitHub.
- Where can I find Failed-ML?
- kennethleungty/Failed-ML is on GitHub at https://github.com/kennethleungty/Failed-ML.