深度学习是 - 翻译成英语

• deep learning is
• for deep learning which is

在 中文 中使用 深度学习是 的示例及其翻译为 英语

尽管物理学家们不认为深度学习是万能的，但一些人认为它可能在应对即将到来的数据处理危机中起到关键作用。
And while physicists don't expect deep learning to be a cure-all, some think it could be key to warding off an impending data-processing crisis.

深度学习是很多人面临的一个挑战，因为它在过去的十年中已经慢慢地改变了形式。
Deep learning has been a challenge to define for many because it has changed forms slowly over the past decade.

现在，深度学习是我们在AI领域所取得成就的顶峰。
Now, in-depth learning is the culmination of our achievements in the field of AI..

如何定义深度学习是很多人面临的一个挑战，因为它的形式在过去的十年中已经慢慢地发生了改变。
Deep learning has been a challenge to define for many because it has changed forms slowly over the past decade.

要详细说明，深度学习是一种机器学习方法，它基于学习数据表示(或特征学习)，而不是特定于任务的学习。
To elaborate, Deep Learning is a method of Machine Learning that is based on learning data representations(or feature learning) instead of task-specific algorithms.

深度学习是人工智能的一种形式，在这种形式中，计算机经过“训练”以做出类似人的决策，而无需对其进行明确的编程。
Deep learning is a form of artificial intelligence, in which computers are"trained" to make human-like decisions without being explicitly programmed for them.

当然，机器学习和深度学习是已经产生重大应用的强大技术，但是，正如所有的热议话题一样，我们应该保持对这一话题的健康的怀疑。
Sure, machine learning and deep learning are powerful techniques with important applications, but, as with all buzz terms, a healthy skepticism is in order.

深度学习是未来.
Deep learning is the future.

深度学习是一项技术。
Deep learning is just a technique.

深度学习是一个黑盒子.
Deep learning is a black box.

深度学习是一个黑盒子.
Deep learning is really a black box.

但是深度学习是一个黑箱。
Deep learning is a black box.

但是深度学习是一个黑箱。
Deep learning is also a black box.

但是深度学习是一个黑箱。
Deep learning is really a black box.

深度学习是增长最快的机器学习领域。
Deep Learning is the fastest growing area of machine learning..

首先，让我们探讨深度学习是什么。
Firstly, let us explore what Deep Learning is.

首先，让我们探讨深度学习是什么。
But first of all, let's define what deep learning is.

深度学习是ML的一个子集。
Deep Learning is a subset of ML.

深度学习是一种全新的软件模式。
Deep learning is a fundamentally new software model.

深度学习是许多可区分系统的组成部分。
Deep learning is a component of many differentiable systems.