In the second course of Machine Learning Engineering for Production Specialization, you will build data pipelines by gathering, cleaning, and validating datasets and assessing data quality; implement feature engineering, transformation, and selection with TensorFlow Extended and get the most predictive power out of your data; and establish the data lifecycle by leveraging data lineage and provenance metadata tools and follow data evolution with enterprise data schemas.阅读更多.
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Machine Learning Data Lifecycle in Production 中涵盖的技术和工具与 数据科学家 招聘广告中的要求最为相似。
Machine Learning Data Lifecycle in Production is a part of 一 structured learning path.
4 Courses
4 Months
Machine Learning Engineering for Production (MLOps)
