What is the translation of " DEEP LEARNING ALGORITHMS " in Chinese?

• 深度学习算法
• 的深度学习算法
• 深入学习算法

Examples of using Deep learning algorithms in English and their translations into Chinese

We are advancing extremely rapidly in perfecting deep learning algorithms.
我们在完善深度学习算法方面进展非常迅速。

Deep learning algorithms try to learn high-level features from data.
深度学习算法尝试从数据中学习高级特征。

This will also facilitate a new class of deep learning algorithms that can detect actions.
这也将促进一种新的深入学习算法，可以检测行动。

Advanced deep learning algorithms can accurately predict what objects are near the vehicle.
先进的深度学习算法可以准确预测车辆附近的物体可能会做什么。

This includes natural-language processing, planning, perception of the environment, and machine and deep learning algorithms.
这包括自然语言处理、规划、环境感知、机器学习和深度学习算法等。

The deep learning algorithms, on the other hand, seek to learn high-level features from data.
深度学习算法尝试从数据中学习高级特征。

Microsoft says that the open source framework is capable of“training deep learning algorithms to function like the human brain.”.
微软表示，开源框架能够“训练深度学习算法，以便像人脑一样工作”。

Deep learning algorithms for detection of critical findings in head CT scans: A retrospective study.
深度学习算法用于检测头部CT扫描的关键发现：回顾性研究.

The artificial intelligence has developed to the current height, and the technically big heroes should belong to deep learning algorithms.
人工智能发展到现在的高度，技术上较大的功臣应该属于深度学习算法。

Current deep learning algorithms and neural networks are far from their theoretically possible performance.
现在的深度学习算法和神经网络，距离理论上可能的表现还很远。

This book will introduce you to some of the most important deep learning algorithms and show you how to run them using Theano.
这里介绍的教程将向您介绍一些最重要的深度学习算法，并将向您展示如何使用Theano运行它们。

But also, advanced deep learning algorithms for 360-degree computer vision that enables situation awareness in all directions.
此外，先进的深度学习算法可用于360度计算机视觉效果，实现各方向面的情境感知。

After comparing data from 14 studies, researchers found that deep learning algorithms correctly detected disease in 87 percent of cases.
在比较了14项研究的数据后，研究人员发现深度学习算法可以正确地检测出87%的疾病。

Tesla had to go out, get more data, annotate that data, add it to the training data set, and re-run the deep learning algorithms.
特斯拉必须上路实测，获得更多数据，对这些数据进行注释，将其添加到训练数据集并重新运行深度学习算法。

Data dependency: In general, deep learning algorithms require a large amount of training data to perform their tasks accurately.
数据依赖性：通常，深度学习算法需要大量的训练数据才能准确地执行任务。

Quartz's app doesn't tailor its responses to your interests; it's based on a flow of content created by human editors, not deep learning algorithms.
Quartz应用不会调整回应以适应用户的兴趣，它基于人类编辑创作的内容流，而非深度学习算法。

Deep learning algorithms can, with surprising accuracy, read human lips, synthesize speech, and to some extent simulate facial expressions.
深度学习算法能以惊人的准确度读取人的唇语，合成语音，并在一定程度上模拟面部表情。

Traditional regression operations may have errors, and deep learning algorithms divide the face into more than 100 key points to avoid errors.
传统回归运算可能会出现误差，深度学习算法则把人脸分为100多个关键点，尽量避免误差。

Weaknesses: Deep learning algorithms are usually not suitable as general-purpose algorithms because they require a very large amount of data.
缺点：深度学习算法往往不适合用于通用目的，因为它们需要大量的数据。

In response, processing chip companies like Nvidia are scrambling to try and produce processors that are specialized to support deep learning algorithms.
作为回应，像英伟达这样的芯片加工企业也正争先恐后地加入进来，尝试生产专门支持深度学习算法的处理器。

Deep learning algorithms differ from other machine learning algorithms in that they use many layers of several types of neural networks.
深度学习算法不同于其他机器学习算法，因为它们使用了许多层的多种类型的神经网络。

Its concepts are a crucial prerequisite for understanding the theory behind Machine Learning, especially if you are working with Deep Learning Algorithms.
它的概念是理解机器学习背后的理论的一个重要先决条件，尤其是在你使用深度学习算法的情况下。

Advanced statistical programs, machine and deep learning algorithms can process this data and generate patterns, trends and implementable business insights.
高级统计程序，机器和深度学习算法可以处理这些数据并生成模式，趋势和可实施的业务洞察。

Deep learning algorithms heavily depend on high-end machines, contrary to traditional machine learning algorithms, which can work on low-end machines.
深度学习算法在很大程度上依赖于高端机器，而传统的机器学习算法可以在低端机器上工作。

Christian Szegedy, Senior Research Scientist at Google: Current deep learning algorithms and neural networks are far from their theoretically possible performance.
ChristianSzegedy，谷歌高级研究员：目前深度学习算法和神经网络的性能与理论性能相去甚远。

Deep learning algorithms can“see” anomalies that traditional rule-based electronic condition monitoring systems miss and can alert rig operations command centers.
深度学习算法可以“看到”传统的基于规则的电子状态监测系统难以发现的异常，并能提醒操作中心和指挥中心。

The company has built deep learning algorithms to analyze imaging and clinical data quickly, enabling it to scan for visual abnormalities in medical scans.
该公司已经打造了深入学习算法来快速分析成像和临床数据，使其能够发现医学扫描中的视觉异常状况。

Deep learning algorithms have also been applied to facial recognition, identifying tuberculosis with 96 percent accuracy, self-driving vehicles, and many other complex problems.
大图深度学习算法也应用于面部识别，能以96%的准确度识别肺结核，自动驾驶汽车，以及其他许多复杂的问题。

Using computer vision and deep learning algorithms, ImageBiopsy Lab is enabling doctors to gain a precise, three-dimensional understanding of two-dimensional images.
通过使用计算机视觉技术和深度学习算法，ImageBiopsy实验室可以使医生就二维图片获得精准的三维理解。

State of the art deep learning algorithms, which realize successful training of really deep Neural Network, can take several weeks to train completely from scratch.
最先进的深度学习算法，实现真正深度的神经网络的成功训练，可能需要几周时间才能完全从头开始进行训练。