What is the translation of " 模型训练 " in English?

• model training
• trained the model

Examples of using 模型训练 in Chinese and their translations into English

TensorBoard是可视化和探索模型训练的一种优秀工具。
Tensorboard is an excellent tool for visualizing and exploring your model training.

变量主要用于在模型训练期间存储和更新值。
Variables are primarily used to store and then update values during model training.

没有GPU，每个模型训练实验将需要几个月。
Without GPUs, each model training experiment would have taken months.

随着模型训练，将显示损失和准确率等指标。
As the model trains, both the loss and accuracy are displayed.

模型训练完成之后，我们就可以对其进行评估了。
After training the model, now we can evaluate it.

异常值往往使模型训练中出现问题。
Outliers often cause problems in model training.

Variable主要用于在模型训练过程中保存和更新值。
Variables are primarily used to store and then update values during model training.

主要有两种任务这样处理：模型训练和中间与最终结果批量计算（batchcomputationofintermediateorfinalresults）。
There are two main kinds of tasks that fall in this category: model training and batch computation of intermediate or final results.

模型训练步骤会在转换后的数据中寻找并存储预测性模式。
The model training step finds and stores the predictive patterns within the transformed data.

至于模型训练，它在PyTorch中需要大约20行代码，而在Keras中只需要一行。
As for the model training itself- it requires around 20 lines of code in PyTorch, compared to a single line in Keras.

机器学习(ML)模型训练过程中使用的观察，包括正确的目标属性值。
The observations used in the machine learning(ML) model training process that include the correct value for the target attribute.

为模型训练而编写新的管道会导致这些SQL查询重复。
Writing a new pipeline for model training leads to duplication of these SQL queries.

除了分离模型训练和模型推理，我们也可以为在线模型训练构建一个完整的基础设施。
Instead of separating model training and model inference, we can also build a complete infrastructure for online model training.

在模型训练中，所有输出序列损失的均值通常作为需要最小化的损失函数。
In model training, the mean of losses for all the output sequences is usually used as a loss function that needs to be minimized.

今年，谷歌和Facebook的开源框架引入了量化，以提高模型训练的速度。
This year, Google and Facebook open source frameworks introduced quantization to increase model training speeds.

今年，Google和Facebook的开源框架引入了量化来提高模型训练速度。
This year, Google and Facebook's open source frameworks introduced quantization to boost model training speeds.

使用AmazonMachineLearning构建机器学习模型的流程包括三项操作：数据分析、模型训练和评估。
The process of building ML models with Amazon Machine Learning consists of three operations: data analysis, model training, and evaluation.

是构建一个完整的机器学习基础设施还是使用已有的框架来分离模型训练和模型推理？?
Do we build a complete machine learning infrastructure covering the whole lifecycle or using existing frameworks to separate model training from model inference?

例如，Facebook、谷歌和优步分别构建了FBLearnerFlow、TFX和Michelangelo来进行数据准备、模型训练和部署。
For example, Facebook, Google and Uber have built FBLearner Flow, TFX, and Michelangelo to manage data preparation, model training and deployment.

对于具有较大数据集的训练任务，分布式计算框架（如MapReduce）通常具有更好的可扩展性，可进行并行化模型训练。
For training with larger dataset, distributed computing frameworks(e.g. MapReduce) are generally used for better scalability and parallelizing model training.

端到端管理，自动化整个预测工作流程，从数据上传到数据处理，模型训练，数据集更新和预测。
End-to-end management, automating the entire forecasting workflow from data upload to data processing, model training, dataset updates, and forecasting.

因此，任何能让科学家在几分钟内从拆箱到进行分布式模型训练的解决方案都是非常可取的。
Therefore, any solution that allows the scientist to go from unboxing to distributed model training in minutes is highly desirable.”.

日前，3D打印医疗模型训练已经在美国泌尿学会的年会上被采纳。
The 3D printed training models have even been used at annual meetings of the American Urological Association.

这帮助模型训练的更快，并且让专家跳过那些对于模型帮助不是很大的数据。
This helps the model learn faster and lets the experts skip labeling data that wouldn't be very helpful to the model(see Figure 5).

这归功于Adam学习方案，它能在模型训练过程中降低学习率，以避免错过最小值。
This also corresponds to the Adam learning scheme that lowers the learning rate during model training in order not to overshoot the optimization minimum.

首先，让我们创建一些变量，以在模型训练的每一步中保持当前对这些值的最佳估计值。
First, let's create some variables to hold our current best estimate of these values at each step of model training.

权重是模型训练过程中学到的价值，并不是所有的节点都有权重。
Weights are the values that are learned during the process of model training, and not all nodes have weights.

模型训练的持续时间和训练频率会有所不同，这取决于用例、数据量和所使用的特定算法类型。
Duration and frequency of model training will vary, depending on the use case, the amount of data, and the specific type of algorithms used.

数据准备和预处理在一个深度学习训练过程中扮演着非常重要的角色，它影响着模型训练的速度和质量。
Data preparation and preprocessing play important roles in the deep learning and training process, and affect the speed and quality of model training.