At this point, our robot has localized itself.

What this says is based on the outcome, we believe for the parameter µ.

We study again our die. You observe the following sequence 1, 2, 3, 2.

You presume correctly.

likelihood. We want to have the most likely albedo and the most likely shape which could give rise to that image.

You mean his alleged suicide.

Also, there'd be more job opportunities there.

We try to evaluate what category that

In this sample, they might derive an estimate on how people are likely to vote.

This Buddhist image cannot be dated exactly.

I guess that she is over thirty.

How dare you presume to...

This is an enormous amount of work.

So if you were 10 you know from the beginning to you're either 50 or 10 if you are 10, then when you go to this guy, he would be able to deduce that he is 30.

Now, it may seem like we made a backwards step.

To do so, I assume that half of the people are of type A and half of the people are of type B.

We find that along the main diagonal our uncertainty has shrunk substantially.

I will now teach you about estimators.

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Supposed suicide.

like when you're trying to guess the number of M amp M's in a jar, but is also an essential skill in math and science, especially when dealing with what are known as Fermi problems.

How would this affect our belief?

Let me ask you again. Suppose you make 111 coin flips.

We find for day 0 we had rain, and maximum likelihood would just say the probability for day 0 is 1.

And what is does is predict how many more species there are on land and in the ocean.

The question is, how can we know where were are with 10 cm accuracy?

SLAM doesn't stand for slamming a robot.

I just want to tell you what you've learned, because you did amazingly well.

Let me give you an algorithm that defines value iteration.

In 3 cases, A is followed by A over here, over here, and over here.

The Vulcans would identify it the moment they inspected the propulsion matrix.

And then we iterate.

W 0, where 0 is your iteration number, and then you up with it iteratively.

And the basis of the fetus' prediction is what its mother eats.

An estimated 23 million people went to the polls today.

It's estimated that Africa loses about 13 billion dollars a year to the disease.

Stop estimating backup size

Simple extrapolation.

An estimated 350,000 people were exposed to the bombing

You really learned a lot about SLAM.

Obviously, it's 1 out of 4. It's 0.25.

In coin flipping, we flip n coins. In elections, we ask n randomly chosen people.

We talked about the Laplace estimator, which added k fake data points, 1 for each possible outcome, and that resulted in the slightly more complex out, as shown in this formula over here. and we identified cases where the Laplace estimator is much better than the maximum likelihood estimator, specifically when there isn't much data.