Two abreast.

That's the first column, that's the second column, that's the third column So, this second matrix we say it is a 2 by 3 matrix.

So that means it's row one column one.

So, this is my design matrix x with x0, the first column being the said term and the second term being you know, my the x values of my three training examples.

So it's getting it's row information from the first matrix's row, and it's getting it's column information from the second matrix's column.

You can also use this to do assignments.

The velocity dispersion versus radius in the lower left and velocity dispersion versus luminosity on the lower right.

Well, how do setup the second column?

left is a 4 by 2 matrix number of rows by number of columns.

The way you get the second column is, well, you take this matrix and you multiply by this second column.

Of this first hypothesis here.

So now let me ask you a question.

And, how about a second column?

That's the first row, that's the second row, and it has three columns.

It's a single row of numbers of a position 1 dimensional.

I am then going to take this matrix on the left, right, so, it will be that matrix, and multiply it by that second column on the right.

So, the maximum of the first column is eight, max of the second column is nine, the max of the third column is seven.

Right this means of

So, this is my second column A, which is 2 4 6.

So, four rows, two columns.

Two passenger trains crashed in Shanghai.

I missed the train by two minutes.

So now let me ask you a question.

So it is the element wise multiplication of two matrices, and in general the P rand tends to, it's usually used, to denote element wise operations in octave.

So to solve for B, first, replace the predicted scores with the observed scores.

Where as in contrast, if you were to take these two matrices, so this one is a 3 by 2 matrix, okay, 3 rows, 2 columns.

I'm going to do is, I'm going to pull out the second column, this matrix on the right and

So, now a is this matrix that's 1, 3, 5.

Does SZ is a one by two matrix whose two elements contain the dimensions of the matrix A. You can also type size A one to give you back the first dimension of A, size of the first dimension of A.

The children went upstairs in single file.

And that's how I formed this matrix C by putting them together.

A one by three matrix of all zeros.

You can make a matrix with a command like this with the argument in the parenthesis.

All the other values should be zero.

So are the measures, are these scores in column one, are they correlated with these scores in column two and so on with column three.

And then I'm going to take the second row of A, 3 5 9, and that becomes the second column. of the matrix A transpose.

You can say that the number if, on the first matrix the number of columns is equal to the number of rows in the second matrix.

A and assign that to 10, 11, 12, and if I do that I'm now, you know, taking the second column of a and I'm assigning this column vector 10, 11, 12 to it.

Another example, 8 1 2 is going to refer to the entry in the first row and the second column and so A 1 2 is going to be equal to one nine one.

I want you to plug in the f matrix.

So, that was the mechanics of how to multiply a matrix by another matrix.

The resulting dimension is going to be that first two times that second two, so the result is itself also a two by two matrix.

We need a thousand more soldiers for the second line of defense!

So, what I'm going to do is, first pull out the first column of my second matrix, that was matrix B, that was my matrix B on the previous slide.

One thing you have to know for multiplication is for, in order to multiply two matrices they have to be what's called conformable.