Superscript

Superscript

Superscript

Superscript

Insert superscript

I and X superscript

In order to distinguish between these different parameter vectors, I'm going to use a superscript 1, superscript 2 there where theta superscript 1 just means the parameters

So I'm also going to use X superscript

So, in this notation, the superscript 2 here.

let me just denote this as theta superscript 1.

So this superscript i over here, this is not exponentiation right?

The inverse is shown like this a negative 1 in the superscript.

The mathematical notation for this is M superscript T, where T means transpose.

Concretely, this means that for every example i I have a feature vector X superscript

Remember, that the parameters in the the neural network of these things, theta superscript I subscript ij, that's the real number and so, these are the partial derivative terms we need to compute.

I write it superscript so there is no confusion with the index i, which is the grid cell.

Number Two. Number Two. Two.

Number...

Number

Number

Number

number

Number

Number

Number

Number

Number

Number

Number

Take a number, any number two.

Favorite number. I love that number.

Mystery number one. Mystery number two

So concretely, this a superscript 2 subscript 1 does the activation of the first unit in layer 2, in our hidden layer.

So that's door number one, door number two, and door number three.

I'm going to use a superscript j subscript i to denote the activation of neuron i or of unit i in layer j.

So I said in the beginning, this kind of is a squared operator. and why do they write it as a superscript there?

Sequence number

F Number

Complex number

Spiral number

Track Number

Disc number

Track number

Disc Number

Track Number