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Identify key components of the ML project lifecycle, pipeline & select the best deployment & monitoring patterns for different production scenarios.Optimize model performance and metrics by prioritizing disproportionately important examples that represent key slices of a dataset.Solve production challenges regarding structured, unstructured, small, and big data, how label consistency is essential, and how you can improve it.
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