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Machine Learning and Data Science : Fundamentals and Applications

2022 - Scrivener Publishing

big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation. [Publisher's Text]

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