In fact, on my desktop are

two files: Features X and

Price Y that's maybe come

from a machine learning problem I want to solve.

So, here's my desktop.

Here's Features X, and

Features X is this window,

excuse me, is this file with two columns of data.

This is actually my housing prices data.

So I think, you know, I

think I have forty-seven rows in this data set.

And so the first house

has size two hundred four

square feet, has three bedrooms; second

house has sixteen hundred square

feet, has three bedrooms; and so on.

And Price Y is this

file that has

the prices of the data in my training set.

So, Features X and

Price Y are just text files with my data.

How do I load this data into Octave?

Well, I just type

the command load Features X dot

dat and if I

do that, I load the Features X

and can load Price Y dot dat. And

by the way, there are multiple ways to do this.

This command if you put

Features X dot dat on that

in strings and load it like so.

This is a typo there.

This is an equivalent command.

So you can, this

way I'm just putting the file name of the string

in the founding in a

string and in an

Octave use single quotes to

represent strings, like so.

So that's a string, and we

can load the file

whose name is given by that string.

Now the WHO command now

shows me what variables I

have in my Octave workspace.

So Who shows me whether

the variables that Octave has in memory currently.

Features X and Price Y

are among them, as well as

the variables that, you know,

we created earlier in this session.

So I can type Features X

to display features X. And

there's my data.

And I can type size features

X and that's my

47 by two matrix.

And some of these size, press

Y, that gives me

my 47 by one vector.

This is a 47 dimensional vector.

This is all common vector that

has all the prices Y in my training set.

Now the who function shows

you one of the variables that, in the current workspace.

There's also the who S

variable that gives you the detailed view.

And so this also, with

an S at the end this also

lists my variables except that it

now lists the sizes as well.

So A is a three by

two matrix and features

X as a 47 by 2 matrix.

Price Y is a 47 by one matrix.

Meaning this is just a vector.

And it shows, you know, how many bytes of memory it's taking up.

As well as what type of data this is.

Double means double position floating

point so that just means that

these are real values, the floating point numbers.

Now if you want to get

rid of a variable you can use the clear command.

So clear features X and type whose again.

You notice that the features X

variable has now disappeared.