AMAZON MACHINE in English translation

有两种方法可以使用AmazonMachineLearning获得预测结果：使用批处理API或实时API。

You can use Amazon Machine Learning to retrieve predictions in two ways: using the batch API or real-time API.

然后，AmazonMachineLearning会使用这些模型来处理新数据并为应用程序生成预测结果。

Then Amazon Machine Learning uses these models to process new data and to generate prognoses for your application.

AmazonMachineLearning(AML)是一个ML服务，提供用于创建ML模型的工具和向导。

Amazon Machine Learning(AML) is an ML service that provides tools and wizards for creating ML models.

作为AI社区的趋势参与者，Amazonmachinelearning在开发自学工具方面提供了高端支持。

Being a trending entrant to the AI community, Amazon machine learning offers high-end support in the development of self- learning tools.

目标属性是训练数据中的一项特殊属性，训练数据包含了AmazonMachineLearning试图预测的信息。

The target attribute is a special attribute in the training data that contains the information that Amazon Machine Learning attempts to predict.

您拥有此临时数据副本的完整所有权，可以在AmazonMachineLearning操作完成后将其删除。

You will retain full ownership of this temporary data copy, and will be able to remove it after the Amazon Machine Learning operation is completed.

例如，AmazonMachineLearning可以根据之前客户的活动来针对目标客户选择最相关的电子邮件广告内容。

For example, Amazon Machine Learning could use prior customer activity to choose the most relevant email campaigns for target customers.

一般来说，为了使用AmazonMachineLearning，首先需要清理数据并将其以CSV格式上传至S3.

In general, you approach Amazon Machine Learning by first uploading and cleaning up your data;

在学习完教程中的内容后，您可以使用AmazonMachineLearning创建您自己的机器学习模型。

After completing the tutorial, you can use Amazon Machine Learning to create your own ML models.

AmazonMachineLearning是一项使任何技能水平的开发者都能轻松使用机器学习技术的服务。

Amazon Machine Learning makes it easy for developers of all skill levels to use machine learning technology.

您可以使用AmazonMachineLearning针对任何模型来计算行业标准的评估指标，帮助了解这些模型的预测质量。

You can use Amazon Machine Learning to compute an industry-standard evaluation metric for any of your models, helping you understand these models' predictive quality.

AmazonMachineLearning的强大算法可通过在您现有的数据中发现模式来创建机器学习(ML)模型。

Amazon Machine Learning's powerful algorithms create machine learning(ML) models by finding patterns in your existing data.

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。

Building machine learning models using Amazon Machine Learning involves three major steps: analysis of data, training models, evaluating models.

AmazonMachineLearning服务控制台提供了强大且易于使用的工具，帮助您发现和理解模型评估的结果。

The Amazon Machine Learning service console provides powerful, easy-to-use tools to explore and understand the results of model evaluations.

AmazonMachineLearning：一个可预测问题的答案的机器学习模型，其中可以二进制变量形式表示答案。

Amazon Machine Learning: A machine learning model that predicts the answer to questions where the answer can be expressed as a binary variable.

AmazonMachineLearning扩展能力极强，可以生成数十亿条预测结果并以极高的吞吐量实时将结果加以运用。

Amazon Machine Learning is highly scalable and can generate billions of predictions, and serve those predictions in real-time and at high throughput.

AmazonMachineLearning：您向AmazonMachineLearning提供的用来练习和评估机器学习模型并生成预测的观察。

Amazon Machine Learning: The observations that you provide to Amazon Machine Learning to train and evaluate a machine learning model and generate predictions.

借助AmazonMachineLearning，您可以使用强大的机器学习技术而无需在机器学习算法和技术领域拥有深厚的背景。

Amazon Machine Learning enables you to use powerful machine learning technology without requiring an extensive background in machine learning algorithms and techniques.

您可以使用AmazonMachineLearning来发现将目标属性连接到交易元数据所存在的规律（所有其他属性）。

You use Amazon Machine Learning to discover patterns that connect the target attribute with the transaction metadata(all other attributes.

例如，AmazonMachineLearning可以用于构建应用程序，使之具有将产品评论分类为正面、负面或中立的功能。

For instance, Amazon Machine Learning could be used to build applications that classify product reviews as positive, negative, or neutral.

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