How to pronounce“datasets”in English

datasets afraid of all that they just want to stay more than theoretical and they're really good at it space I don't know if

So datasets are great.

unlimited datasets but similar to many four-year-olds it takes me months or years to acquire proper coordination skills also like humans

better datasets to understand how to improve like sustainability on all social aspects.

email datasets naturally contains uses social security numbers and credit card

Let's take public datasets and identify how we can more clearly map vectors and then express that information to health care

from massive datasets with real privacy guarantees for all the people's information that are in that data set.

of big datasets.

cross-country datasets that are ...

and big datasets, by the way, also Stanford, ImageNet, to sort of come together and, and create this sort of extraordinary explosion that's gonna shape the future.

You're getting huge datasets, you can't even adjust them, so all it has to get outsourced, the consultants and it makes for

interesting the datasets at the time on the biology side were much more interesting both from a technical and also from an aspirational perspective

these open datasets of protein how did that with the protein databank

She does a project called Missing Datasets.

The point is this is datasets that we can use to analyze pitching performance, the movement of the baseball.

They have to be trained on massive datasets.

And we've been building datasets and tools to help investors understand risk and return forever.

Because while some of these datasets have constructed them, once you create a fuller panel, you're going to have to fill in the gaps.

But they're then downloading datasets off of the web, and the Y is given, and the X is given, and they're using X to predict Y.

being able to visualize those datasets all those kinds of stuff just working with data and now we're starting to talk about

learning and I were using datasets that frankly we're not very inspiring some of us old-timers still remember the quote-unquote twenty newsgroups dataset

So here you see a lot of folders full of missing datasets.

She keeps a GitHub repository where she has these missing datasets.

How do you make it be a part of the datasets that you're-- the problem sets you're working on?

We merged these datasets.

And so the code for reading in large datasets and treating them like tables or belonging in white, then you can do in Stata, I don't use Stata, it's really nice there.

then this coverage is really going to vary across these datasets.

those squishy things into digital data into beautiful datasets but so that data

And so one thing that's really important in these very large datasets is first identifying what are the cognitive chunks.

And what we're increasingly finding is a lot of bias and inequity in the datasets that were being used, and as a result of that,

I did a big project with mobile location data on this huge datasets and I could just spin up a server on Amazon and

You can learn about us hopefully it will be the US because our datasets the richest.

For example, a recent study of massive text datasets found that in the early 1900s, Asians in the US were characterized with words like barbaric or

that's kind of exciting because I'm so most of my days spent with datasets that

And they found an accuracy of-- I think it's over 90% in identifying high-risk women just from public datasets.

So here, we played a similar game with two UCI datasets, iris and breast cancer.

Now it can also recreate the hit trajectory, and that's where we're getting these datasets from-- the velocity of the hit, and the distance of the hit,

out an independent research report that we wrote about our understanding of what was in those datasets.

medicine, but also how well it's performing on your own datasets, on your own demographic.

We talked to Rebecca Diamond, who's an economist and Rebecca uses large datasets.

wanted the data to train it and also is fully auditable so that you can see what datasets you're using to train the model.

So, for this purpose, we need to access two datasets.

And there are many problems settings, you'll see this if you work with the datasets provided in the class, where you might go look for heterogeneous treatment effects, and

I'm also going to try to spend a little bit of time as possible on creating your own datasets, and try to convince you that the barriers there aren't as high as you

So security volumes are a little bit more difficult, but within some of these datasets, you'll be able to reconstruct the volume of flows.

However, in high dimensional data, and in many typical datasets that we may work with that have a very high number of covariates.

The point here is that we put those stipulations in that you're not allowed to combine these datasets with any other.

It consisted in locking myself up in a library, looking at datasets, and running regressions.

You just want to be able to do more experiments faster and do so with bigger datasets, right?