What is the translation of " COMPLEX DATASETS " in Chinese?

• 复杂的数据集

Examples of using Complex datasets in English and their translations into Chinese

Ability to analyse large and complex datasets;
分析大型,复杂性的数据；.

More complex datasets naturally give rise to varied and interesting visualizations, including overlaid graphs of different kinds.
更复杂的数据集自然会产生各种有趣的可视化效果，包括不同种类的重叠图形。

Work with real, large and complex datasets..
使用真实，大型和复杂的数据集.

Quickly understand large and complex datasets using advanced statistical procedures ensuring high accuracy to drive quality decision-making.
使用高级统计程序快速了解大型和复杂的数据集，确保高精度以提高质量-决策.

Its strength is continent-wide analysis of complex datasets.
其能力是大陆范围内的复杂数据分析。

Work with simple and complex datasets common to Scikit-Learn.
使用Scikit-Learn通用的简单和复杂数据集.

It focuses on deep learning, and the design of self-teaching systems that can learn from large, complex datasets.
它侧重于深度学习，并设计了可从大型复杂数据集中学习的自学系统。

These professionals typically interpret larger, more complex datasets, that include both structured and unstructured data.
这些专业人员通常需要研究更大、更复杂的数据集，包括结构化和非结构化数据。

It focuses on deep learning, and the design of self-teaching systems that can learn from large, complex datasets.
该课程侧重于深度学习，以及可以从大型复杂数据集中进行学习的自学系统设计。

They can easily work with their largest, most complex datasets, speeding workflows and allowing for interactive collaborative reviews.
他们能够轻松处理最庞大、最复杂的数据集，从而加快工作流程，进行交互式协作检查。

Skinner has hired permanent bioinformatics personnel to assist the lab members in reviewing complex datasets.
目前，斯金纳教授已经专门聘请了生物信息学专业背景的固定人员来协助实验室进行复杂数据的审核。

DNNs(an advanced form of machine learning particularly applicable to large, complex datasets) are what make smart machines appear“intelligent.”.
DNNs（特别适用于大型复杂数据集的一种高级机器学习形式）是使智能机拥有“智能”。

The course focuses on deep learning along with the design of self-teaching systems that can learn from large, complex datasets.
它侧重于深度学习，并设计了可从大型复杂数据集中学习的自学系统。

DNNs(an advanced form of machine learning particularly applicable to large, complex datasets) is what makes smart machines appear"intelligent.".
深度神经网络（是一种高等形式的机器学习，尤其适用于复杂的大型数据集）就是让智能设备看起来“聪明”的关键所在。

The course focuses on deep learning along with the design of self-teaching systems that can learn from large, complex datasets.
该课程侧重于深度学习，以及可以从大型复杂数据集中进行学习的自学系统设计。

To extract the information embedded in complex datasets, Data Scientists employ a number of tools and techniques including data exploration, visualisation, and modelling.
为提取复杂数据集中的信息，数据科学家采用了许多工具和技术，包括数据探索、可视化和建模。

By applying this five-step method, it is possible to investigate large and complex datasets without being an expert in statistics.
通过应用这个五步法，科学家就可以研究大量复杂的数据集，而不必成为统计专家。

We want to encourage data sharing among businesses to solve common problems, drive innovation and unlock the value of complex datasets.
其次，我们必须利用数据的价值，鼓励企业互相分享数据，目的是解决共同的问题，推动创新，展现复杂数据集的价值。

Hazy's solution is a game changer, enabling businesses to automatically anonymize complex datasets without the need for a lengthy technical integration with internal systems.
Hazy的解决方案是改变游戏规则，使企业能够自动对复杂数据集匿名化处理，而无需与内部系统进行冗长的技术集成。

AI can provide earlier warnings for conditions like seizures or sepsis, which often require intensive analysis of highly complex datasets.
人工智能可以为癫痫病或败血症等疾病提供早期预警，这通常需要对高度复杂的数据集进行深入分析。

Deep learning networks can analyze complex datasets and provide rich insights in areas such as early detection, treatment planning, and disease monitoring.
深度学习网络能分析复杂的资料集(Dataset)，并在早期发现(EarlyDetection)、治疗规划(TreatmentPlanning)及疾病监测(DiseaseMonitoring)等领域提供丰富的洞察力。

Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets.
学习使用强大的开源python工具，包括熊猫、git和matplotlib，来操作、分析和可视化复杂的数据集。

Despite recent progress in generative image modeling, successfully generating high-resolution, diverse samples from complex datasets such as ImageNet remains an elusive goal.
尽管近期由于生成图像建模的研究进展，从复杂数据集例如ImageNet中生成高分辨率、多样性的样本仍然是很大的挑战。

A candidate will learn how to use powerful, open source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets.
学习使用强大的开源python工具，包括熊猫、git和matplotlib，来操作、分析和可视化复杂的数据集。

Despite recent progress in generative image modeling, successfully generating high-resolution, diverse samples from complex datasets such as ImageNet remains an elusive goal.
尽管生成图像建模最近取得了进展，但从ImageNet等复杂数据集成功生成高分辨率、多样化的样本仍然是一个难以实现的目标。

Every reasonably complex dataset we have seen contains imperfections.
我们所看到的每一个复杂度适中的数据集都存在缺陷。

In the next iteration, we will include a simple bidding mechanism in combination with more complex queries for datasets.”.
在下一次迭代中，我们将纳入一个简单的招标机制以及更复杂的数据集查询。