What is the translation of " 模型学习 " in English?

• model learns
• model learning

Examples of using 模型学习 in Chinese and their translations into English

模型学习出合理的权重。
The model learns reasonable weights.

模型学习将图像与标签相关联。
The model learns to associate images and labels.

让模型学习得到它。
Let the model learn from it.

计算模型学习如何预测材料缺陷.
Computational models learn how to predict material defects.

我们发现这些模型学习语言的基本属性，”彼得斯说。
We found that these models learn fundamental properties of language,” Peters says.

训练完成后，该模型学习最佳方案的参数。
Once training was complete, the model learned parameters for optimal regimens.

我们发现，这少量的权重衰减对于模型学习是重要的。
This small amount of weight decay is important for the model to learn.

换句话说，该模型学习如何从原始数据中自动提取对正在解决的问题直接有用的特征。
In other words, the model learns how to automatically extract the features from the raw data that are directly useful for the problem being addressed.

从那里，模型学习一个“空间”的所有可能的信号，可以产生一个给定的投影。
From that, the model learns a“space” of all possible signals that could have produced a given projection.

这种模型学习类似于模拟器构建，它可以帮助AI代理通过“想象”进行规划。
This model learning is analogous to building a simulator, which helps the agent to plan by imagining.

底部）讯息投射模型学习，将回复语句与相应传入讯息的投射联系在一起。
(Bottom) The message projection model learns to associate replies with the projections of the corresponding incoming messages.

重要的是，通过应用分布式查询，我们能够简化模型学习问题。
Importantly, by applying distributed querying answering we are able to simplify the model learning problem.

该模型学习临床解释的主题水平表示，反映疾病的严重程度。
The model learns a clinically interpretable subject-level representation that is reflective of the disease severity.

本文探讨了一种用于机器学习的通用数据管道，其中涵盖了数据工程、模型学习和操作。
This article explored a generic data pipeline for machine learning that covered data engineering, model learning, and operations.

同样的，许多的无参数器学习算法也包括限制约束模型学习概念多少的参数或者技巧。
As such, many nonparametric machine learning algorithms also include parameters or techniques to limit and constrain how much detail the model learns.

训练完成后，该模型学习最佳方案的参数。
By the end of the training, the AI model had learned the parameters for optimal regimens.

直观地说，多任务学习鼓励模型学习对许多任务有用的表述。
Intuitively, multi-task learning encourages the models to learn representations that are useful for many tasks.

为此，研究人员强迫该模型学习没有主题信息的特征。
To that end, the researchers forced the model to learn features without subject information.

您希望模型学习“如果两家咖啡店相同，则选择更近的一家”。
You would like the model to learn,“if two cafes are the same, prefer the closer one.”.

这鼓励模型学习更有意义的词对表示，而不是更一般的目标，如语言建模。
This encourages the model to learn more meaningful representations of word pairs than with more general objectives, such as language modelling..

预训练步骤帮助模型学习可以在目标任务上重用的一般特性，从而提高其准确性。
The pretraining step helps the model to learn general features that can be reused on the target task, boosting its accuracy.

这就激励了模型学习更有意义的词对表示，而不使用语言建模等更通用的目标。
This encourages the model to learn more meaningful representations of word pairs than with more general objectives, such as language modelling..

我们发现，这少量的权重衰减对于模型学习是重要的。
We found that this small amount of weight decay was important for the model to learn.

特定任务层：尽管把MTL用于NLP的标准方法是硬参数共享，但允许模型学习特定任务层很有意义。
Task-specific layers While the standard approach to MTL for NLP is hard parameter sharing, it is beneficial to allow the model to learn task-specific layers.

用于控制过拟合，因为较高的深度将允许模型学习对于特定样品的特定关系。
Used to control over-fitting as higher depth will allow model to learn relations very specific to a particular sample.

我们发现小的学习衰减率对于模型学习是非常重要的。
We found that this small amount of weight decay was important for the model to learn.

他们使用条件变化的自动编码器，或“生成模型”，机器学习模型学习生成类似于它训练的合成数据。
They used conditional variational autoencoders, or"generative models," machine learning models which learn to generate synthetic data similar to that which it is trained on.

然后，将车道标记预测作为辅助任务，强制模型学习它们的表征；.
Predicting lane markings as auxiliary task, however, forces the model to learn to represent them;

他迫使模型学习什么是重要的。
He sort of forced the model to learn what's important.