Learning in sentence

2412 examples of Learning in a sentence

Companies like LinkedIn and Facebook sometimes will tell you about who your friends might be and you have no idea how it did it, and this is because it's using the power of machine learning.

We don't know how to write those programs by hand, but with machine learning, this is now possible.

One of the most amazing examples I've seen of machine learning happened on a project that I ran at Kaggle where a team run by a guy called Geoffrey Hinton from the University of Toronto won a competition for automatic drug discovery.

They used an extraordinary algorithm called deep learning.

Deep learning is an algorithm inspired by how the human brain works, and as a result it's an algorithm which has no theoretical limitations on what it can do.

The New York Times also showed in this article another extraordinary result of deep learning which I'm going to show you now.

(In Chinese) (Applause) Jeremy Howard: Well, that was at a machine learning conference in China.

Everything you saw there was happening with deep learning.

The transcription in English was deep learning.

The translation to Chinese and the text in the top right, deep learning, and the construction of the voice was deep learning as well.

So deep learning is this extraordinary thing.

In this obscure competition from Germany called the German Traffic Sign Recognition Benchmark, deep learning had learned to recognize traffic signs like this one.

In 2012, Google announced that they had a deep learning algorithm watch YouTube videos and crunched the data on 16,000 computers for a month, and the computer independently learned about concepts such as people and cats just by watching the videos.

Humans don't learn by being told what they see, but by learning for themselves what these things are.

For example, Google announced last year that they had mapped every single location in France in two hours, and the way they did it was that they fed street view images into a deep learning algorithm to recognize and read street numbers.

Baidu is kind of the Chinese Google, I guess, and what you see here in the top left is an example of a picture that I uploaded to Baidu's deep learning system, and underneath you can see that the system has understood what that picture is and found similar images.

In fact, deep learning has done more than that.

Complex, nuanced sentences like this one are now understandable with deep learning algorithms.

Deep learning now in fact is near human performance at understanding what sentences are about and what it is saying about those things.

Also, deep learning has been used to read Chinese, again at about native Chinese speaker level.

As I say, using deep learning is about the best system in the world for this, even compared to native human understanding.

Here is some text that I generated using a deep learning algorithm yesterday.

Each of these sentences was generated by a deep learning algorithm to describe each of those pictures.

In each of those two cases, they were systems developed by a combination of medical experts and machine learning experts, but as of last year, we're now beyond that too.

The system being shown here can identify those areas more accurately, or about as accurately, as human pathologists, but was built entirely with deep learning using no medical expertise by people who have no background in the field.

We can now segment neurons about as accurately as humans can, but this system was developed with deep learning using people with no previous background in medicine.

With our deep learning algorithm, it can automatically identify areas of structure in these images.

Now, these deep learning systems actually are in 16,000-dimensional space, so you can see here the computer rotating this through that space, trying to find new areas of structure.

So we do that for a while, we skip over a little bit, and then we train the machine learning algorithm based on these couple of hundred things, and we hope that it's gotten a lot better.

So we can again give the computer some hints, and we say, okay, try and find a projection that separates out the left sides and the right sides as much as possible using this deep learning algorithm.

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