The road across the mountain was narrow, and what's more, it was a steep slope.

It's on very steep ground.

Maximum gradient

B is going to be his next position so this is how the hill climber decides where to go next.

It makes sense because it's a downward sloping line, but it's not too steep.

Now, they tell us what the slope of this line is.

It is able to move around its environment.

I think when we go through these, it will be pretty self explanatory.

Draw scrollbar bevel

It sends out that at local optimum your derivative would be equal to zero.

Is it linear or nonlinear?

What is his method going to be?

And essentially, the apartments cover the parking.

Notice also that on all of these graphs, the slope is steeper on in group, authority, purity.

So at any point, the gradient is a vector.

Now, we can use that exact same logic

This angle plus this angle is going to be equal to this angle.

Now, my derivative term, d, d theta one j of theta one, when evaluated at this point, gonna look at right.

Sixpercent grade, fast greens, breaks to the left.

Now the other thing that we know

But there is a very curious pattern in the rest of the 20th century, because we see a sharp decline in this Islamic modernist line.

Now what else can we figure out?

And if you want to eye ball where is equivalence point, you look for the steepest point in the graph.

That's where the derivative is.

And it turns out there are sometimes other versions of gradient descent that are not batch versions but instead do not look at the entire traning set but look at small subsets of the training sets at the time, and we'll talk about those versions later in this course as well.

Arc angle

Shadow Angle

In B, it's about zero.

Degrees

Radius

Angle

Angle

X angle

Y angle

Angle

X angle

Y angle

Do I do it upside down?

Obviously, this is a right angle

So we could draw that here.

How can we describe this mathematically?

And that's the best angle of the courtyard?

So if you apply the rule over here, if you were to start at A as your W zero, then your gradient is negative.

An angle of 90 degrees is called a right angle.

Some people would call this the reflexive property