Navigating Model Deployment and Data Challenges in Machine Learning

This chapter explores the complexities of deploying machine learning models, emphasizing the transition from traditional training methods to utilizing open-source models and APIs. It highlights the challenges faced in data collection, particularly in high-stakes scenarios like chip testing at Intel, and the need for robust infrastructure to manage diverse data streams.

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