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It is projected that every day humans produce approximately 2.5 quintillion bytes of data each day. With this insane amount of new data, surely some of it must be redundant, right? For data science, analytics, and machine learning, this increase in the amount of data available leads to previously unthinkable new avenues for research. But while more and more data is being harvested for a variety of reasons, could better curation of the data we have already collected lead to better outcomes for research? Read on
Identifying new scientific datasets can be a time consuming, but necessary, step to perform complex machine learning tasks. Why not apply machine learning methods to automate the indexing of datasets itself? Read on

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