Security for Data Scientists
summary
Covers practical security concerns relevant to data scientists, including how to protect data, models and code using tools and practices from the Python ecosystem; explains threats and concrete measures (e.g., access control, encryption, secure deployment) that can be applied during data analysis and machine learning workflows.
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