深度学习模型 - 翻译成英语

• deep learning models
• deep-learning model
• deep learning model
• deep-learning models

在 中文 中使用 深度学习模型 的示例及其翻译为 英语

因此，一个可解释的深度学习的研究机会是将人类的知识结合起来，以提高深度学习模型的鲁棒性。
Accordingly, one research opportunity concerning explainable deep learning is to incorporate human knowledge to improve the robustness of deep learning models.

透过应用你的深度学习模型，银行可能会大大减少客户流失。
By applying my Deep Learning model the bank may significantly reduce customer churn.

AWS和微软上个月宣布了在ApacheMXNet上的一个新Gluon接口计划，该计划允许开发人员构建和训练深度学习模型。
AWS and Microsoft last month announced plans for Gluon, a new interface in Apache MXNet that allows developers to build and train deep learning models.

该研究利用深度学习模型进行早期探查，可以发现未来6-18个月内导致心力衰竭的情况和阶段。
The research uses a deep learning model to allow earlier detection of the incidents and stages that often lead to heart failure within 6-18 months.

它还消除了放射科医师对用于训练大多数深度学习模型的大型高质量数据集进行注释的需要。
It also eliminates the need for radiologists to annotate the large, high-quality data sets used to train most deep learning models.

用不良数据训练深度学习模型会引发创建具有内在偏见和不正确或令人反感的结果的系统的真实可能性。
Train a deep learning model with bad data introduces the very real possibility of creating a system with inherent bias and incorrect or objectionable outcomes.

借助易于使用的RESTAPI，您可以根据用户需求或预算，使用不同数量的资源来训练深度学习模型。
With easy-to-use REST APIs, you can train deep learning models with different amounts of resources per user requirements or budget.

DeepLearningStudio可以自动地为您自定义的数据集设计深度学习模型，这要归功于我们先进的AutoML功能。
Deep Learning Studio can automagically design a deep learning model for your custom dataset thanks to our advance AutoML feature.

Keras确实更具可读性和简洁性，使你可以更快地构建自己的第一个端到端深度学习模型，同时跳过实现细节。
Keras is indeed more readable and concise, allowing you to build your first end-to-end deep learning models faster, while skipping the implementational details.

相比之下，Keras提供了一种简单方便的方法来构建深度学习模型。
In contrast, keras provides a simple and convenient way to build a deep learning model.

它提供了更高级别，更直观的抽象集合，使得开发深度学习模型变得容易，无论使用的计算后端如何。
It offers a higher-level, more intuitive set of abstractions that make it easy to develop deep learning models regardless of the computational backend used.

这些特征没有经过训练，当网络训练一组图像时，它们重新学习，这使得深度学习模型对于计算机视觉任务非常准确。
They』re learned while the network trains on a set of images, which makes deep learning models extremely accurate for computer vision tasks.

自1月开始，麻省总医院筛查中心的放射科医生便已经开始在其临床工作流程中使用深度学习模型。
Since January, radiologists at Mass General screening centers have been using the deep learning model as part of their clinical workflow.

Intel®深度学习框架：与Tensorflow*和Caffe*一起用于训练深度学习模型的框架和API。
Intel® Deep Learning Framework: A framework and API for training deep learning models in conjunction with Tensorflow* and Caffe*.

在接下来的几篇文章中，我们将训练计算机视觉+深度学习模型来进行面部识别。
In the next couple of blog posts we are going to train a computer vision+ deep learning model to perform facial recognition….

序贯模型的API在大多数情况下非常适合开发深度学习模型，但也有一些限制。
The Sequential model API is great for developing deep learning models in most situations, but it also has some limitations.

矩阵相乘(MatrixMultiplication)--几乎所有的深度学习模型都包含这一运算，它的计算十分密集。
Matrix Multiplication- This exists in almost all models of Deep Learning and is computationally intensive.

深度学习模型的一大优点是特征提取是“自动化”的。
One of the great advantages of a deep learning model is that feature extraction is'automatic'.

深度学习模型的典型示例是前馈深度网络或多层感知器（MLP）。
The quintessential example of a deep learning model is the feedforward deep network or multilayer perceptron(MLP).

分析乳房X光片时，放射科医生会看到深度学习模型做出的评估，并决定是否与其保持一致意见。
When analyzing mammograms, radiologists see the assessment made by the deep learning model and decide whether or not to agree with it.