What is the translation of " MASSIVE DATA SETS " in Chinese?

• 海量数据集
• 大量数据集

Examples of using Massive data sets in English and their translations into Chinese

The issue at hand now is how to manage these massive data sets.
现在面临的问题是如何管理这些庞大的数据。

This has led to the rise of massive data sets generated by millions of computers.
这掀起了数百万台计算机产生的大量数据集的热潮。

Powerful instruments, such as accelerators, produce massive data sets.
加速器等强大仪器能产生巨型数据集。

It is able to handle massive data sets, which can aid marketers in a number of ways.
它能够处理大量数据集，从而可以通过多种方式帮助营销人员。

The applications vary in size, but some use massive data sets.
这些应用大小不一，但其中一些使用了大规模的数据集。

Data: Our massive data sets must become a genuine competitive advantage for Yahoo!
数据：我们的海量数据必须要成为雅虎的竞争优势。!

Both these technologies are great at identifying patterns from massive data sets.
这两种技术都非常擅长从大量数据集中识别模式。

This system can accurately analyze massive data sets to make sure the inventory of each product and each store is optimized.
该系统可以准确分析海量数据集，确保每个产品和每个商店的库存都得到优化。

And“Drill” will help Hadoop users achieve faster querying of massive data sets.
而“Drill”将有助于Hadoop用户实现更快查询海量数据集的目的。

These massive data sets can be difficult to obtain or create for many business use cases, and labeling remains a challenge.
对于很多业务用例而言，这些海量数据集很难获取或创建，并且标记仍是一个难题。

What if, instead, they shared their tools- and more importantly, the massive data sets they have assembled?
相反，如果他们共享他们的工具--更重要的是，共享他们已经收集的大量数据集呢?

When massive data sets are used to train AI systems, the individual images and videos involved are commonly tagged and labeled.
当大规模数据集被用来训练人工智能系统，其中涉及的个人图像和视频通常会被打上标注。

Open source technology is helping organizations of all sizes convert massive data sets into meaningful business intelligence.
开源技术正在帮助各种类型和规模的组织将大数据集转换为有意义的业务情报数据。

The AI-enabled hardware of Summit will allow researchers to train and operate neural networks and process massive data sets.
Summit的支持AI的硬件将允许研究人员训练和操作神经网络并处理海量数据集。

Scientists and researchers can manipulate massive data sets and complex simulations, visualizing data up to 5 times faster.
科研人员可操作大量数据集和复杂模拟，数据可视化的速度提升最高达5倍。

What ties all the threads together, says Kelly, is an effort to provide''decision support using AI[that analyzes] massive data sets.''.
Kelly说，将所有的线索联系在一起的，是努力“使用AI（分析）海量数据集的决策支持”。

This includes anything with massive data sets, such as BI, analytics, and AI/ML, because moving it to the cloud is expensive.
这包括任何具有大量数据集的东西,如BI、分析以及AI/ML,因为将其移动到云计算是昂贵的。

What ties all the threads together, says Kelly, is an effort to provide''decision support using AI[that analyzes] massive data sets.''.
Kelly表示，将所有线程连接在一起的是一种努力，即“使用人工智能分析大量数据集的决策支持。

Predictive analytics use machine learning to pull together massive data sets,“learn” from the past, and make predictions about the future.
预测分析使用机器学习将大量数据集合在一起，从过去“学习”，并对未来做出预测。

You must have both massive data sets and specialists with decades of training to ensure that the computer models are up to difficult tasks.
你必须要有大量的数据组，以及几十年经验的老专家，才能确保计算机的模型能够应对复杂的任务。

No more subjective opinions or guesswork; decisions will be based on AI working with massive data sets to create a truly competitive industry.
不再有主观臆断或臆测，决策将基于AI与海量数据集的合作，以创建真正有竞争力的行业。

Supporting modern computers and massive data sets: Unlike manual processes, machine learning doesn't assume that the world is full of straight lines.
支持现代计算机和海量数据集：与手工流程不同，机器学习不假设世界充满了直线。

In the harsh realities of the business world, a cloud OS offers the compute and storage capacity needed to handle massive data sets with ease.
在商业世界的严酷现实中，云计算操作系统提供了轻松处理大量数据集所需的计算和存储容量。

Massive data sets require special thought: some cloud-based providers cap the sizes of stored files, and data-transfer and storage costs can become prohibitive.
庞大的数据集需要特殊的考虑:一些基于云的提供商限制了存储文件的大小，数据传输和存储成本可能变得令人望而却步。

The massive data sets obtained from the hardware, operating systems, server software and application software can be aggregated and correlated to find insights and patterns.
从硬件、操作系统、服务器软件和应用软件中获得的大量数据集可以被聚合和关联，以发现洞察力和模式。

Computer programmes analysed the massive data set(believed to comprise the largest wildlife survey in the world) in order to individually identify each animal.
计算机程序分析了大量的数据集(据信是世界上最大的野生动物调查)，以便个别地识别每一种动物。

Within this massive data set, many more planets are likely to be lurking, and quote possibly within multi-planetary systems that have already been surveyed.
在这个庞大的数据集中，更多的行星可能潜藏着，并且可能在已经被调查过的多行星系统中引用。

Thus for this study, we used just 31 high-definition cameras, but still were able to build a massive data set.”.
对于这项研究，我们只使用了31个高清相机，但仍然能构建一个庞大的数据集。