But he actually got a state-of-the-art sentiment analysis classifier out of it.

但他其实由了一个最先进的情感析。

And I realized it's not just made of models and classifiers for the neural network.

我意识到它不仅是神经网络的模型和屏。

And in this module we have a class called decision tree classifier.

在这个模块中，我们有一个名为决策树的。

He said, " There's really not much we could say at this point about how the classifier actually works."

“关于该的实际工作原理，我们真的不能说太多。”

Through our editorial team, through our semantic classifiers, through what the community tells us they do or they don't want.

通过我们的编辑团队、我们的语，以及通过网络社区告诉我们他们想要什么或不想要什么。

Indulge your astonishment, my friend, and have a look, because there's plenty of work here for a classifier of your talents.

朋友，你惊奇吧，你好好地看吧，因为对于你这么能干的一个者，这里实在有不少的工作可哩。

Now, the classifier says, " Is this cancer or is this not cancer? "

现在，说，“这是癌症还是不是癌症？”

We see that the classifier comes back with a pretty similar prediction.

我们看到返回了一个非常相似的预测。

You train the classifier on ImageNet, let's say.

你在ImageNet上训练，比如说。

OpenAI has classifiers that recognize when there's a prompt that's indicating self-harm.

OpenAI设有，能够识别暗示自残的提示。

This decision process is called classification, and an algorithm that does it is called a classifier.

这个决策过程称为，执行这一过程的算法称为。

So, at the end, let's create an object called models nd set it to anew instance of decision, tree classifier. Like this.

所以，最后，让我们创建一个名为模型的对象， 并将其设置为一个新的决策实例，即树。 像这样。

Based on the classifier's guesses the drawing system then tweaks the image and feeds it through again.

根据的猜测，绘图系统然后调整图像并再次输入。

In order to train our machine learning classifier to make good predictions, we’re going to need training data.

为了训练我们的机学习以良好的预测，我们需要训练数据。

Plus, a truly useful classifier would contend with many different moth species.

外，一个真正有用的需要应对许多不同的蛾物种。

But you could probably reformulate with all the same data and make a classifier lying or not.

但你可以用同样的数据重新构建一个，来判断是否在撒谎。

And then now you immediately get a classifier out of this, right?

于是现在，你便能立即从这之中得到一个，对吧？

Existing classifiers, trained for things like facial recognition or self-driving cars, are used to spotting objects that loom large in their field of vision.

现有的受过面部识别或自动驾驶汽车等方面的训练，可用于发现在他们的视野中逼近的物体。

In addition, the RGB-DSIFT-LLC features were input into a linear support vector machine (SVM) classifier for identifying the maturity of fruits.

外，RGB-DSIFT-LLC特征被输入到一个线性支持向量机（SVM）中，用于识别水果的成熟度。

One of the things that Mike Schneider's working on right now is an image classifier at a relatively small scale.

迈克·施耐德目前正在研究的是一种规模相对较小的图像。