39 Lessons on Building ML Systems, Scaling, Execution, and More
Read OriginalThis article compiles 39 lessons from 2024 machine learning conferences, focusing on building and scaling production ML systems. It covers practical topics like defining reward functions, knowing when to use ML, managing trade-offs, setting realistic expectations, handling temporal data, and the importance of evaluation frameworks and data flywheels for sustainable product improvement.
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