英語 での Large datasets の使用例とその 日本語 への翻訳
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Batch predictions are designed to be run against large datasets asynchronously, using services such as Cloud Dataflow to orchestrate the analysis.
Finally, in addition to studying rare events and studying heterogeneity, large datasets also enable researchers to detect small differences.
The team at the Federal University of Rio de Janeiro, Brazil, looked at large datasets comparing the total number of neurons of different species, as well as cortical surface area, thickness, brain volume, and amount of folding.
Quite simply, researchers who don't think about systematic error face the risk of using their large datasets to get a precise estimate of an unimportant quantity, such as the emotional content of meaningless messages produced by an automated bot.
In a blog post, Microsoft's Dare Obasanjo shared his notes on a session given by Jeff Dean from Google at the Google Seattle Conference on Scalability,“MapReduce, BigTable, and Other Distributed System Abstractions for Handling Large Datasets”.
With over a petabyte of the world's leading public satellite imagery data available at your fingertips, you can avoid the cost of storing the data and the time and cost required to download these large datasets and focus on what matters most: building products and services for your customers and users.
For example, some companies apply simple models to large datasets, some apply complex models to small ones, some need to train their models on the fly, and some don't use(conventional) models at all.
Finally, 2014 saw the use of new techniques to study cell signaling and identify drug targets, such as the in vivo use of RNA interference to study signaling in T cells and new computational methods to study large datasets of different data types.
One of the advantages of having both vBlock and Isilon is that we can use Isilon for deep storage of our really large datasets. Yet on the vBlock we have the flexibility to run very high performance applications but also to have very tight integration with the data store on the backend.”.
Mixed-Precision Computing Double the throughput and reduce storage requirements with 16-bit floating point precision computing to enable the training and deployment of larger neural networks. High Speed HBM2 Memory Built with 16GB of the industry's fastest graphics memory(717 GB/s peak bandwidth), Quadro GP100 is the ideal platform for latency-sensitive applications handling large datasets.
Labelme: A large dataset of annotated images.
We obtained a very, very large dataset.
The necessary overview in larger datasets, the management program with different search filters and the option will to take address data in groups.
Why: The capacity to handle larger datasets gives you more flexibility on the data you choose.
Accurate facial recognition algorithms are based on deep learning and require a large dataset to train the system.
You can even toggle connections with a click to apply in-memory queries to the larger dataset.
The best way to deal with these misclassifications is use the largest dataset possible.
Our creative approach and large dataset enabled us to calculate weather-related reductions in gestational lengths across the entire U. S.
Send your largest datasets directly to your machine learning tools of choice via Stream Results.
Baidu Apolloscapes: Large dataset that defines 26 different semantic items such as cars, bicycles, pedestrians, buildings, street lights, etc.