机器学习任务 in English translation

• machine learning tasks
• machine-learning tasks
• machine learning task

Examples of using 机器学习任务 in Chinese and their translations into English

这些机器学习任务是在CloudDataproc中运行的，CloudDataproc是一个运行ApacheSpark的服务。
These machine learning jobs are run in Cloud Dataproc, a managed service that runs Apache Spark.

一旦将业务问题分解为机器学习任务，一个或多个算法可以用于解决给定的机器学习任务。
Once we have broken down business problems into machine learning tasks, one or many algorithms can solve a given machine learning task..

学习针对机器学习任务的单个滤波器是一种强大的技术。
Learning a single filter specific to a machine learning task is a powerful technique.

这些模型已经被证明对许多机器学习任务有效，特别是知识库的完成。
Such models have proven to be effective for a number of machine learning tasks, notably knowledge base completion.

监督学习是一类机器学习任务，它有一个已知的目标。
Supervised learning is a type of machine learning task where there is a defined target.

为了使这些概念更具体，让我们来看看机器学习任务的一些非常简单的例子。
To make these ideas more concrete, let's take a look at a few very simple examples of a machine learning task.

这些例子的目的是，给出本章将要介绍的机器学习任务类型的直观，非定量的概述。
These examples are meant to give an intuitive, non-quantitative overview of the types of machine learning tasks we will be looking at in this chapter.

无监督的学习是另一类机器学习任务，它没有目标。
Unsupervised learning is a class of machine learning task where there are no targets.

前面提到的包是Python机器学习任务的核心;
The aforementioned packages are again, subjectively the core of a wide array of machine learning tasks in Python;

值得注意的是，这里的重点是在本地设备上执行机器学习任务。
Notably, the focus here is on doing machine learning tasks on the local device.

除了用于分析和调试等程序员的工具之外，甚至可以实现机器学习任务的自动区分。
Beyond instrumentation for programmers like profiling and debugging, this can even implement automatic differentiation for machine learning tasks.

他们被称为环境，因为他们为执行机器学习任务提供了图形用户界面,但也提供了Javaapi供使用者开发自己的应用程序。
They are called environments because they provided graphical user interfaces for performing machine learning tasks, but also provided Java APIs for developing your own applications.

报告摘要：越来越多的机器学习任务需要处理大型图数据集，这些数据集捕获了潜在数十亿元素之间的丰富而复杂的关系。
Abstract: An increasing number of machine learning tasks require dealing with large graph datasets, which capture rich and complex relationship among potentially billions of elements.

LightGBM是一种快速、高性能的梯度提升框架，其基于决策树算法，可应用于排序、分类和许多其他机器学习任务。
Light GBM is a fast, distributed, high-performance gradient boosting framework based on decision tree algorithm, used for ranking, classification and many other machine learning tasks.

LightGBM是一种快速、高性能的梯度提升框架，其基于决策树算法，可应用于排序、分类和许多其他机器学习任务。
LightGBM: A fast, distributed, high performance gradient framework is based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

拥有50多个处理器和加速器，运行着超过1亿行代码，来支持计算机视觉、规划和其他机器学习任务。
They have more than 50 processors and accelerators running more than 100 million lines of code to support computer vision, planning, and other machine learning tasks.

机器学习任务.
Machine Learning Tasks.

机器学习任务通常分为几大类：.
Machine learning tasks are typically classified into several broad categories.

大多机器学习任务是关于预测的。
Most Machine Learning tasks are about making predictions.

DMTK使得机器学习任务很容易进行扩展。
The DMTK is designed to allow machine learning tasks to be easily scaled.