All right. E, F, L, E, P, T P, L, E, P, F, L, E L, E, P, T, L, P, E, F, E, T, Z, E, T...

P R E V I E W

And right here, this environment is called PyScripter.

So e to the r.

like one, or two.

P of D given C is 2 parameters for P of D given C and P of D given not C.

And that's called a mixed strategy.

It makes sense to E to push that up at high as possible since H is the maximizer.

So that becomes the new P, so I could write Pe to the r, and it's going to and that new principal is going to compound for another year.

We can multiply by that term once rather than having it in each row of the table.

If I were to borrow it for another year, it becomes Pe to the 3r.

And a lot of times you'll hear people talk about a stock's P E Ratio.

Suppose we have the parsing state

And the sentences are P or not P, P and not P,

And then this term over here, this whole thing over here, is going to be plus p times 1 is p. p times negative 2p is negative 2p squared.

And then this formula, which most people, frankly, just memorize, this Pe to the rt, will make a lot of sense to you, and you will have a permanent neuron for it the rest of your life.

Let's say that this is our grammar

And if you want to factor a p out of this, this is going to be equal to p times, if you take p divided p you get a 1, p square divided by p is p.

Once again, based on this P, I'm going to start bringing in rules 1 and 2.

When we pass that to printallelements, the variable p will refer to that object.

Then we continue in the loop.

Now in probability terms, people often write it as follows

F, L, E, P, T, P L, E, P, F, L, F, L, E, P, T, P, L, F, E, T.

We're just going to, we're just going to skim probability theory for now.

like we hinted at here with our purple text, we will also be here.

Over here we see one that's very similar

Let me just do this over here.

We're going to go through the elements of p.

So chart state 0 includes the following parse states

And one of our previous states in chart B had been

Remember, you've got an infinite number of choices for any value for P.

Well, now we seen enough input to actually make a single (E).

We might see parentheses right after seeing a minus sign that's valid for this language.

So that cancels out.

So this is going to be equal to 1 minus p.

So here, E goes to end becomes E goes to dot end from 2, that looks really good.

In the book, I talk about how you're wired to do certain things, you're SHAPED with a little acrostic

One of the elements of chart 2 is

Another way to think about that is let's say that we're in a particular state like this one

P of A given B where B is the evidence and A is the variable we care about is P of B given A times P of A over P of B.

Say we have 1 2 3. We can do this in 2 ways.

P of X3 given X1 is the sum of P of X3 given X1 and A times P of A given X1 plus the A complement, which is X3, conditional X1 and not A times P of not A given X1.

Magic trick of perspective if I read from the bottom up we're generating or producing strings.

This stays the same.

(E gt E E) so this option may look very tempting.