Aug. 31, 2023, 1:27 a.m. | Durgesh kumar prajapati

DEV Community dev.to

Building successful data science projects is not straightforward and sometimes it can turn into a nightmare. There are many challenges from data ingestion to production, including feature engineering, modeling, testing, deployment, and infrastructure management. Until a few years ago, data scientists were trying to deal with all these challenges on their own, but they were having a hard time overcoming them. To address these challenges, new fields such as data engineering, feature engineering, and machine learning (ML) engineering have emerged. …

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