[MUSIC] So what we're gonna do next is #Let's show what our predictions look like. Now I talked about using GraphLab Canvas
as a way to visualize data, but you can also use other tools out there
to visualize; other python tools. So just as a simple demonstration of that,
I'm going to import one search tool. It's a pretty commonly used one. It's called mot plot lib. And so, and from there I'm gonna input something called pipe plot which
allows you to do some plotting in Python. And I'm gonna refer to it as PLT. So when you're doing the importing Python,
if you type import myplotlib.pyplot, is a particular piece of the package,
and I write as plt. Now I don't have to write this whole
thing matlab_lib.pyplot blah blah blah, I just write plt. That's why we use the as command. So I'm gonna import it, and one little
trick I'm gonna do, just like you did with Canvas to make sure it prints inside
the notebook I'm gonna do it here too. So you put this percent, and you say, matplotlib inline. So that just plots it
on the notebook itself. So let's hit Enter. We've imported it, and
now I'm going to actually build a map plot lib plot for the results,
for the initial results. So we're gonna plot plt.plot. And there's a function here. And I'm gonna plot my
test data in two ways. So it's interesting, can plot two multiple
plots on top of each other with MyPlot 11. We're just gonna do that together. So I'm gonna take my test data and
in my test data I'm gonna plot on the x-axis
the square feet of living space. And in the y-axis for my test data,
I'm going to plot the price. So, this is kind of similar to the plot
we did above, the scatter plot. And I'm gonna refer to each one
of these points as test points. I'm gonna draw them as a dot. So, that's what this little dot here does. However, I'm also going
to plot one more thing. So I'm going to plot two
things on the same plot. Actually, so I'm missing a comma up here. So in addition to plotting the test data,
let's plot our predictions. So again, on the x-axis is going to
be the square feet of living space, but on the y-axis,
I'm going to plot something else. I'm going to plot what my model
predicted for each one of those houses. So remember we built this
square foot model and it has many functions associated with it. If you go down, one of those functions
it has is called the predict function. And the predict function, you can
give it a bunch of data's input and it's gonna output and estimates our
column of data with the predictions for each one of these input elements. So, I'm giving you the test data and
I'm going to draw it as a dash. Now, before I execute this line, just take a moment to imagine what
this plot is going to look like. So, the top line says plot living space
through the price test data with dots. It's going to look very similar to
the scatterplot that we drew before. And the second line says plot the input houses living with
the prediction with a dash. And now remember this was a simple linear
regression model with a single variable so all we have is a single variable and as we covered in the lectures,
we just plotted a single line. And we'll see that execute and
here we are. So the blue dots here
are the test data for the houses, while the green line corresponds
to the predicted house values. [MUSIC]