ml-for-high-risk-apps-book/Machine-Learning-for-High-Risk-Applications-Book
Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
This project provides practical code examples for managing the risks associated with AI and machine learning systems. It helps you understand and apply techniques for responsible AI development, taking raw ML models and data as input to produce more reliable, fair, and secure AI applications. It's designed for data scientists and ML practitioners who are building or overseeing AI in sensitive areas.
106 stars. No commits in the last 6 months.
Use this if you are a data scientist building AI systems and need to ensure they are robust, fair, and compliant with ethical and regulatory standards.
Not ideal if you are looking for a pre-built, ready-to-deploy AI solution rather than educational resources for improving your own ML applications.
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Jupyter Notebook
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MIT
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May 23, 2023
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