Original subtitles

Hi, everyone, and welcome in this new video.

In this video, we're all going to see the main point of this chapter, which is the training of our

linear regression, though we have already seen the theory behind the linear regression.

And even for those of you which are not very comfortable with this notion, you will see that the practice,

it's really much easier.

To create a linear regression, we need to import the linear regression class from psychedelia to do

it.

We use the from import operator.

So from psychic points linear model, we want to import the class linear regression.

Then we need to initialize the class to do it.

We're going to create a variable containing this class, and I have chosen to begin this course with

their first model as a linear regression because we don't need to specify some parameter.

So it's really much easier to you to understand your first machine learning algorithm so you don't need

to put any parameters because the few parameters for this class is set by default.

And then to fit the model, we just needed to use the function of the ranking class.

So in parameters, we need to give the feature so extreme and the target because a linear regression

is a supervised machine learning model.

So it means that to between

the algorithm needed extremes of the features and the target to compute and never function, and then

change its parameters to minimize this error.

So we need to put the target and then we are currently train or algorithm.

And in the next video, we're going to do some prediction, some stock price prediction using this linear

regression.