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Summary: The fundamentals of Data Engineering encompass essential practices like datamodelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?
A Machine Learning Engineer is crucial in designing, building, and deploying models that drive this transformation. billion by 2031, growing at a CAGR of 34.20%. Model Evaluation and Tuning After building a Machine Learning model, it is crucial to evaluate its performance to ensure it generalises well to new, unseen data.
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