机器学习在90年代早期开始进入工业领域。
Machine learning started making its way into industry in the early 90s.
机器学习在90年代早期开始进入工业领域。
Machine learning started making its way into the industry in the early 90s.
机器学习的基本限制在于，需要从大量过去的数据中学习。
The fundamental limitation of machine learning is that it needs to learn from large volumes of past data.
温斯顿说：“机器学习往往提供更可靠的统计形式，使数据更有价值。”
"Machine learning often provides a more reliable form of statistics which makes data more valuable," says Winston.
通常，这会导致产品出故障，引起市场怀疑，对机器学习的完整性造成打击。
This usually results in a failure of a product, which leads to skepticism from the market and delivers a blow to the integrity of Machine Learning technology.
人工智能和机器学习有巨大的潜力，可以通过将这些技术整合到全球的关键市场来彻底改变农业。
There is huge potential for artificial intelligence and machine learning to revolutionize agriculture by integrating these technologies into critical markets on a global scale.
因此，在传统的数学和物理基础课题之外，应该增加一门融合了计算机科学、编程、统计学和机器学习的新学科。
Therefore, a new discipline blending computer science, programming, statistics and machine learning should be added to the traditional foundational topics of mathematics and physics.
然后，该系统利用多种机器学习技术进行自我培训，以便以一种近乎即时的方式对众多短文或答案进行自动评分。
The system then uses a variety of machine-learning techniques to train itself to be able to grade any number of essays or answers automatically and almost instantly.
其分析工作涉及到统计推断及机器学习技术的应用。
The analytical work involves applying statistical inference and machine learning techniques.
在机器学习中，数据通常被表示为矢量，有时也称作特征矢量。
In machine learning, the data is often represented as a vector, sometimes called a feature vector.
广告系统使用计算机影像和机器学习元素来交付目标广告体验。
AD system USES elements of computer vision and machine learning to deliver a targeted advertising experience.
语音、视觉、机器人学、传感器和机器学习等不同学科的融合。
Integration of separate fields such as speech, vision, robotics, sensors and machine learning.
日志文件分析在机器学习和监控工具领域是一个非常热门的主题。
Log file analysis is a hot topic in machine learning and monitoring tools.
提苏尔发明的程序利用了一种名为“机器学习”的计算机策略。
为大脑编写程序，微软主要依靠人工智能的前端领域—机器学习。
In programming this brain — a process that's still going on-microsoft relies on an advancing field of artificial intelligence called machine learning.
机器学习可以应用于各种目的，从游戏、欺诈检测到股票市场分析。
Machine learning USES run the gamut from game playing to fraud detection to stock-market analysis.
在机器学习方面，我们需要给机器提供带有情绪和表情的很好的声像材料。
In terms of machine learning, we had to give the machines good audiovisual material with real emotions and expressions.
不过此后，由机器学习方面专家所设计的算法就能接班，开始自动设定温度。
But after that, algorithms designed by machine learning experts, set the temperature automatically.
在本文中，我将重点讨论Mahout当前已实现的三个具体的机器学习任务。
For this article, I'll focus on three specific machine-learning tasks that Mahout currently implements. They also happen to be three areas that are quite commonly used in real applications.
机器人已经能够通过机器学习能力教会自己微笑、皱眉以及其他的人类面部表情。
A robot has taught itself to smile, frown, and make other human facial expressions using machine learning.
每个星期，他们在Hadoop科研集群上重新计算他们关于类别的机器学习模式。
Every week they recompute their machine learning models for categories in a science Hadoop cluster.
卡耐基·梅隆大学的机器学习和人工智能教授汤姆·米切尔表示，这次会议改变了他的观点。
Tom Mitchell, a professor of artificial intelligence and machine learning at Carnegie Mellon University, said the February meeting had changed his thinking.
在简要概述机器学习的概念之后，我将介绍ApacheMahout项目的特性、历史和目标。
After giving a brief overview of machine-learning concepts, I'll introduce you to the Apache Mahout project's features, history, and goals.
此外，还有许多公司在自己的应用程序中应用了机器学习，以便学习用户以及过去的经验，从而获得收益。
Many, many more companies would benefit from leveraging machine learning in their applications to learn from users and past situations.
这其中就蕴含着机器学习领域以及本文章所介绍项目的前景：ApacheMahout（见参考资料）。
Therein lies the premise and the promise of the field of machine learning and the project this article introduces: Apache Mahout (see Resources).
到目前为止，众多有关机器学习的文章中一个重要的主题是利用算法对训练数据进行总结归纳，而不是简单的记忆。
So far, a major theme in these machine learning articles has been having algorithms generalize from the training data rather than simply memorizing it.
机器学习的目标并不完全是寻找意识那么刺激，不过从某些方面说，它更有可能接近达到传统人工智能研究的目标。
The goal of machine learning is not quite the search for consciousness that seems so exciting, but in some ways it comes closest to reaching for what may seem to be the traditional goals of AI.
然后，我将演示如何使用Mahout完成一些有趣的机器学习任务，这需要使用免费的Wikipedia数据集。
Then I'll show you how to use Mahout to do some interesting machine-learning tasks using the freely available Wikipedia data set.
然后，我将演示如何使用Mahout完成一些有趣的机器学习任务，这需要使用免费的Wikipedia数据集。
Then I'll show you how to use Mahout to do some interesting machine-learning tasks using the freely available Wikipedia data set.
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