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Episode 32: Building Reliable and Robust ML/AI Pipelines

Vanishing Gradients

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Effective Anonymization with Local Models

An individual encountered a challenging task involving financial data for a friend's nonprofit. To maintain privacy, they used a local model to anonymize the data by replacing any identifiable information. This method proved effective, highlighting the importance of understanding what information needs to be anonymized instead of directly requesting anonymization. The process showcased the nuances of working with language models compared to human reasoning.

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