But there's a fair bit of variation around it, so I would say that the relationship is linear but not exact.

We have to actually create a new variable. And I, I'll cover this in more detail when

This setting is known as Kentucky Compensation.

Just recall what a positive and negative relationship are a couple of simplified examples.

What I come up with are forms like these.

So many teenagers are looking for love which, love does heal the soul,

It's totally outofbounds.

His form... perfect.

He is quite clearly out of danger.

We've lost the ship!

And we knew that it involved this square.

Totally, totally.

Totally dead. Way dead.

Now, this thing that we have here is exactly that pattern.

So you get 4 times y squared minus 4y.

So essentially we want this, we want the left hand side to have this form.

Which is great, you know, I'm not knocking girls.

liter

linear

lightyears

Linear

Perfectly coordinated, it has resulted in the utter rout of the Eurasian army.

I would say a lot easier than what we did in the previous first order homogeneous difference equations, or the exact equations.

The forces of Oceania in south India have won a glorious victory.

Linear Sweep

Y linear

Linear Scale

Reset curve to linear

Where the idea is that the given data points like this, and we seek to find a linear subspace in which to perfect the data.

Because I squared, I multiplied the second derivative of y with respect I multiplied it times itself.

Full

Completely?

Much.

It says that, if it were linear, the steepest slope, then doubling the size you would require double the amount of energy.

If pixels are negative, we just ignore the negative sign and map back to the absolute value.

It's kind of perfectly symmetric in every way.

How about our Gaussian kernel that we discussed in class of size 5 by 5?

And I'll quickly review the linear algebra you need in order to implement and use the more powerful versions of linear regression.

Is that perfectly clear to you?

All of it.

We sure are.

Now the second thing we have to figure out is this linear or is this a non linear differential equation?

First is our gradient kernel here minus 1, 1.

Linear

Linger after solving