机器学习项目 - 翻译成英语

• machine learning projects
• machine learning project

在 中文 中使用 机器学习项目 的示例及其翻译为 英语

这门课也有两个“流程模拟器”，可以让你作为机器学习项目的领导者，练习如何决策。
This course also has two“flight simulators” that let you practice decision-making as a machine learning project leader.

你会学到深度学习的基础，理解如何创建神经网络，学习怎么成功地领导机器学习项目。
You will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects.

那时，实际上很难找到数据科学和机器学习项目的数据集。
Back then, it was actually difficult to find datasets for data science and machine learning projects.

我喜欢“动手机器学习”，它可以让你通过机器学习项目从开始到结束。
What I like about Hands-On Machine Learning is that it takes you through a machine learning project from beginning to end.

在一天结束的时候，会有一些机器学习项目成功，有些失败。
At the end of the day, some machine learning projects succeed and some fail.

第一次尝试机器学习的人通常会惊讶于实际花费在机器学习项目上训练的时间如此之少。
First-timers are often surprised by how little time in a machine learning project is spent actually doing ma-.

机器学习渴望，AndrewNg博士目前正在撰写的一本免费书籍，教你如何构造机器学习项目。
Machine Learning Yearning, a free book that Dr. Andrew Ng is currently writing, teaches you how to structure machine learning projects.

也就是说，到2022年，这些企业机构预计将平均部署35个人工智能和机器学习项目。
In other words, by 2022, organizations plan to have an average of 35 AI or machine learning projects in place.

正如我们以后会看到的那样，机器学习项目中的某些选择甚至比学习器的选择更加重要。
As we will see, some choices in a machine learning project may be even more important than the choice of learner.

导致许多机器学习项目成功和失败的主要因素就是使用了不同的特征。
The factor that makes the biggest difference between machine learning projects that fail and succeed it is the features used.

机器学习项目可能不是线性的，但它有许多典型的步骤：.
The process of a machine learning project may not be linear, but there are a number of well-known steps.

本文的目标读者是已经从事机器学习项目的数据科学专业人员。
The target audience for this article is data science professionals who are already working on machine learning projects.

如果你刚开始进行机器学习项目，我会建议你先从scikit-learn开始。
If you're just getting started with a machine learning project, I would recommend that you first start with scikit-learn.

在您知道这些问题(以及其他简单但重要的业务问题)的答案之前，您还不应该进行机器学习项目。
And until you know the answer to these questions(and other simple but important business questions), you should not go for machine learning projects yet.

但是，并非所有机器学习repo都使用Python：GitHub上的一些常用语言也是机器学习项目的常用语言。
However, not all machine learning happens in Python: some of the most common languages on GitHub are also common languages for machine learning projects.

机器学习数据集知识库(MachineLearningDatasetRepository)由集合了由参与机器学习项目的数据科学家贡献的开放数据集。
Machine Learning Dataset Repository Collection of open datasets contributed by data scientists involved in machine learning projects.

但是，并非所有机器学习repo都使用Python：GitHub上的一些常用语言也是机器学习项目的常用语言。
However, not all machine learning projects use Python: some of the most common languages on GitHub are also the common language for machine learning projects.

报告发现，最终，71%的团队表示他们将培训数据和其他机器学习项目活动外包出去。
Of the teams confirmed that they outsource training data and other ML project activities.

经过五门课程的学习后，您将掌握深度学习的基础知识，了解如何构建、优化和部署神经网络，同时掌握如何成功领导机器学习项目。
In 5 courses, you will learn the foundations of deep learning, understand how to build neural networks, and learn how to lead successful machine learning projects.

而且，由于我们主要探讨督导式学习，因此，训练数据的缺乏依然是机器学习项目的首要瓶颈，这一点毫不意外。
Moreover, since we're dealing mainly with supervised learning, it's no surprise that lack of training data remains the primary bottleneck in machine learning projects.