We could talk about government data, enterprise data is really important, there's scientific data, there's personal data, there's weather data, there's data about events, there's data about talks, and there's news and there's all kinds of stuff.

But it's not about questions. It's about data.

And it's because I'm giving you critical data about me.

We talk about drowning in data.

So statistics is all about data.

You may be given some data points, and you might worry about what is the best Guassian fitting the data?

Let's think about data for a bit.

In fact, data is about our lives.

It's about a year's worth of data.

So it is with data. I could talk about all kinds of data.

Data, data, data...

So say you have a lot of data and you wanted to tell someone about it without giving them all of the data.

So what can scientists learn about this data?

Bing! That's data. Data, data, data.

And this is when you use data to essentially make conclusions about things.

That would correspond to about 50 megabytes of data, which is small when you think about the data we can handle today just on normal mobile devices.

That would correspond to about 50 megabytes of data, which is small when you think about the data we can handle today just on normal mobile devices.

So if you think about the amount of data that is being produced today, database systems are handling terabytes of data, sometimes even terabytes of data every day.

You will have data.

If you could comment a little bit about where Big Data is coming from.

Perhaps you don't share my excitement about looking at data and using simple tools

And that is what linked data is all about.

How do you move data around and operate with data?

What do you mean, data ? What's the difference documents, data?

You have data, and data in neuroscience is sensory input.

If you're going to be storing lots of data, try to think about how you store data in individual tables. gt gt Okay.

I am excited about cloud data, where you can use Scratch to store data online and create project with high score and surveys

In both cases you're given data, but in 1 case you have labeled data, in another you have unlabeled data.

We talked about the fit from data and we even talked about multivariate Gaussians.

You know, a data network.

You can mix data type.

Here you see the data.

The discussion is all about images on the computer, data.

Now let's talk a bit about how to manipulate data.

And I know 200, I know about the small data.

So think about the data from a crisis text line.

Other data has the music industry at about 45,000 people.

It's really great about the real world as we gain more data like the world wide web or medical data sets or financial data sets.

Think about how much of that data is about how life is lived in America.

I will give you data and you will plot those data and answer simple questions.

You can take data from different sources and try to understand the information in that data, what the data is telling you.

Warning Your data is about to be transmitted across the network unencrypted. Are you sure you wish to continue?

I'm going to talk some about how computers actually store data.

There's a concept that people talk about nowadays called big data.

It's kind of like Irene talking about Google being data driven.