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The new draft code also outlines the licensing framework public authorities must use when making their datasets available for re-use.
We were fortunate to receive permission from StockTwits Inc. to have access to their datasets.
We use the their proposed models and their datasets with the learned parameters.
Companies brag about the size of their datasets the way fishermen brag about the size of their fish.
End users are able to view the costs of storage of each of their datasets.
Sophisticated users sometime shard their datasets on the application level, but this can get very complex and error prone.
Google, Facebook, Twitter, Zynga, and more, already have their datasets living in memory and backed-up on disk.
The proposed scheme allows data providers to outsource their datasets to a cloud service provider with low communication cost.
To check the performance of existing methods we used their datasets and developed QSAR models using HIVprotI approach.
In contrast, providing storage capacity to manage and preserve their datasets had not been considered in depth.
In particular, companies that monetize on targeting data may find very quickly that they can enrich their datasets through features that are not necessarily well-documented.
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