在 中文 中使用 监督式 的示例及其翻译为 英语
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目前，人工智能主要是监督式学习，有监督的训练就需要带标签的数据，因此数据的质量和精准度与输出结果密切相关。
At present, AI is mainly supervised learning, 通过监督式学习，反向传播算法能够识别输入到输出映射中的错误，然后相应地调整权重（通过学习率）来纠正该错误。
Backpropagation, through supervised learning, identifies an error in the input-to-output mapping, and then adjusts the weights accordingly(with a learning rate) to correct this error.简而言之，它指出没有任何一种算法能够适用每一个问题，而且它对于监督式学习（即预测性建模）尤其重要。
In a nutshell, it states that no one algorithm works best for every problem, and it's especially relevant for supervised learning(i.e. predictive modeling).监督式机器学习需要标记数据.
Supervised machine learning requires labeled data.分类被认为是监督式学习。
Classification is considered supervised learning.他们采用的就是监督式学习。
They are using supervised learning.这就是所谓的监督式学习。
That's called supervised learning.监督式学习问题会有两种类型：.
Supervised learning problems can be of two types.监督式的机器学习模型具有卓越的预测能力。
Supervised machine learning models boast remarkable predictive capabilities.回归和分类都属于监督式学习的示例。
Classification and regression are the examples of supervised learning.监督式的机器学习模型具有卓越的预测能力。
Supervised machine-learning models boast remarkable predictive capabilities.集群和主题建模都是非监督式学习的示例。
Clustering and association are examples of unsupervised learning.确实，自编码器并不是一种监督式学习；.
And indeed, autoencoders are not a form of supervised learning;例子：监督式学习有两种形态的模型。
As with supervised learning, there exists two models.我们发现，几乎所有人都使用监督式学习算法。
We note that almost everyone uses supervised learning algorithms.我们已经从监督式学习中创造了巨大的商业价值。
We have already created tremendous value from supervised learning.当人们谈论人工智能时，他们通常并不意味著监督式和非监督式机器学习。
When people talk about artificial intelligence, they usually don't mean supervised and unsupervised machine learning.在监督式学习中，样本的“答案”或“结果”。
In supervised learning, the"answer" or"result" portion of an example.监督式学习问题可以进一步被分为回归和分类问题.
Supervised learning can further be categorized into regression and classification problems.在监督式训练中，模型从有标签样本中进行学习。
In supervised training, models learn from labeled examples.
