Challenges in building machine learning systems include creating and maintaining the model, handling data quality, and deploying the model to production. MLOps is about the culture and practices of building and maintaining machine learning systems. Basic investments in testing, CI/CD, and git hygiene can bring significant gains in development velocity and production reliability.
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