Abstract
Machine Learning is increasingly being applied to many different application domains. From cancer detection to weather forecast, a large number of different applications leverage machine learning algorithms to get faster and more accurate results over huge datasets. Although many of these datasets are mainly composed of array data, a vast majority of machine learning applications do not use array databases. This tutorial focuses on the integration of machine learning algorithms and array databases. By implementing machine learning algorithms in array databases users can boost the native efficient array data processing with machine learning methods to perform accurate and fast array data analytics.
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