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MLOps focuses on the intersection of data science and data engineering in combination with existing DevOps practices to streamline model delivery across the ML development lifecycle. An Amazon Comprehend flywheel automates this ML process, from dataingestion to deploying the model in production.
Strategies for Overcoming Challenges Now that we understand the hurdles, let’s explore strategies to overcome them and successfully scale Data Science projects. Prioritize Data Quality Implement robust data pipelines for dataingestion, cleaning, and transformation.
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