Kaggle, ML Community / Engineering (Sanyam Bhutani)
Machine Learning Street Talk (MLST)
00:00
From Models to Production: Bridging the Data Science Divide
This chapter explores the multifaceted lifecycle of data science and machine learning, emphasizing the essential roles of data engineering, MLOps, and infrastructure in deploying effective models. The speakers discuss the gap between innovative model building and the engineering expertise needed for successful deployment, advocating for standardized practices and automation to streamline workflows. Through personal anecdotes and discussions on reproducibility and testing, they highlight the importance of cross-discipline collaboration and the balance necessary in managing complex machine learning projects.
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