Data Formats

Data Format

Not if the data's in different formats.

Depending on your usage scenario, add more access rights as you see fit.

I mean, the whole data was there, you know?

Toxic spirals

I'm not going to get into the details of how you store these various pieces of data, the point is that you can do so.

Let's think about data for a bit.

Valid date formats

Really, in my mind, it's very similar to depreciation.

Obviously , a machine you can't do all of those things to it, but you can at least touch it and possibly smell and taste it.

So now that we've issued commands to the player, let's try to get some data from it. Useful data to have is what the current time of the player is, how far the user is in the video.

If I type in some junk or forget to validate my passwords, I get an error message.

Easy to find and easy to share

Gather some meaningful statistics

And institutions can learn from this.

There're a lot of elements.

Note

Now, fortunately there are methods to search efficiently.

Depreciation is tangible.

So, hello.mat, what we did just now to save hello.mat to view, this save the data in a binary format, a somewhat more compressed binary format.

In this case, the entire front half of the subject has been synthesized.

It gives us more data that we can use.

I can assure you that chances are in your favor.

I can assure you that chances are in your favor.

Throw it into the audience again.

You say, This photograph, it's about it depicts this person.

Obviously, it's impossible to put a line through the data points over here.

I will get back some data in a standard format which is kind of useful data that somebody might like to know about that thing, about that event.

Really cool!

Thrun It's interesting to see how to minimize a loss function using gradient descent.

So let's dive straight in so let's talk about lines and let's talk about the technology to fit lines to data called linear regression.

In this case, the problem really comes down to the naive Bayes assumption is a weak one, and the Markov assumption would do much better.

like this with positive and negative examples, this data is linearly separable and by that, I mean that there exists, you know, a straight line, altough there is many a different straight lines, they can separate the positive and negative examples perfectly.

One of its diagonals will be right along the horizontal, right like that.

It's the one within the artificial intelligence I love the most.

The government doesn't release the accurate figures of radiation. MAN Thank you very much. Thank you for working so hard.

But based on what data?

There's no rocket science here.

In this case, I would submit this is probably the most suitable linear subspace.

Everything that makes you a Person, turn it into pure data

In our interpretation, the output data in Table 2 is an acceptable variation of that in Table 1.

The infectious diseases Cochrane Group, which are based in Italy, has been trying to get the full data in a usable form out of the drug companies so that they can make a full decision about whether this drug is effective or not, and they've not been able to get that information.

We'll be able in the next few videos to develop more powerful forms of linear regression that can view of a lot more data, a lot more features, a lot more training examples and later on after the new regression we'll actually continue using these linear algebra tools to derive more powerful learning algorithims as well

But what's it's doing is sharing data.