Your uncertainty shrinks to 3.99, which is slightly better than the measurement uncertainty.

Forecast

If that guy's going down to zero, I'll know.

These are old faculty salaries.

XTide Tide Predictor

Monthly estimates

Before, when we just did simple regression, that was our equation.

There's also a measurement update step where we use the measurement z.

And they estimated that in 2008,

And this is what the inevitable problem looks like.

So this scenario makes predictions.

So this happens in physics all the time.

What's our time frame?

I don't know what you do.

Anticipation.

That's a bit unusual.

This should be very familiar to you.

Suppose he predicts you'll go there.

Agent Farnsworth is running scenarios.

And then I'll observe again the 2.

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Here are my best guesses. Okay?

Try to feel his next movement.

Take upstairs.

We're expecting resistance

You were right all along. You were right before anybody.

I am just going to show you two. So we have, our first one is uh, we can predict why from the mediator variable.

We can just conclude that. This more complex model.

In state estimation that's a really fancy word for just computing the probability of the internal or hidden state given measurements.

So instead, I decided to go for a lab.

Do research where two models are competing against one another.

We knew there was a measurement update and a motion update, which is also called prediction.

We actually think the future's going to be event driven.

So that's a toggler.

You can follow it through the fossil record.

And who knows?

Have you anydea how he intends to do that?

You won't see the next one coming either.

What I did is, I emailed essentially anyone that has anything to do with pancreatic cancer.

Yes, well, we dream on a budget here, don't we?

In Kalman filters we iterate measurement and motion.

The other equation is the prediction equation, so let's go from X1 to X2.

And the crypto theme is

There's a new covariance matrix, and for the third observation followed by the prediction, the prediction is correctly effectively 4, 3.999.

So, in the last lecture we talked about simple regression.