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https://doi.org/10.1007/978-1-4842-6405-8Azure; Data Scientist; DevOps; Azure Databricks; data abstraction; Big data analytics后退 发表于 2025-3-23 15:33:00
978-1-4842-6404-1Julian Soh and Priyanshi Singh 2020机构 发表于 2025-3-23 20:58:25
Clinical Diagnosis: “Simple” Patientst innovation, such as machine learning (ML), artificial intelligence (AI), and Internet of Things (IoT). This is not an inaccurate representation since data science is after all the foundation for ML, AI, and IoT.crockery 发表于 2025-3-24 01:07:50
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https://doi.org/10.1007/978-3-030-44703-8livery and quality of model development through monitoring, validation, and governance of machine learning models. This is equivalent to how DevOps helps software engineers develop, test, and deploy software quicker and with fewer defects. MLOps supports the data science life cycle just as DevOps su人造 发表于 2025-3-24 18:48:45
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Statistical Techniques and Concepts in Data Science,e been brought together to solve a business problem, optimize a process, or create predictive models based on data-driven techniques. It is thus imperative that all members of the team have some idea of the statistical techniques and concepts used in data science.