All language subtitles for 4. Features engineering process

Everyone and welcome in this new video in this video, we're going to do a little features engineering

on the Google stock price to do it.

I have just copy paste, the function created in the previous chapter, so as remain that we're going

to create the return of the Google stock price.

The simple moving average and the volatility.

So the moving of volatility and the RSI.

So.

We are going to put

this new variable in another that are free to don't have any interference in all data, and it's very

important to do it like this all the time to really avoid some issues in your court.

So as we can see, it's already easy to create a new variable.

And it's also necessary to create it because it will be very difficult for all algorithm to find the

same pattern.

For example, just with the close column.

So, for example, to predict tomorrow, using just the price of today, the algorithm needed to have

a larger visualisation, for example, using the same may or the moving volatility or many other indicators.

But here it's really just an example.

So we have enough indicator, but in a real life project, you can add more indicator and you, for

example, a PCI on that.

So.

If you want, for example, and then date with the PC, don't hesitate to tell me in the comments of

the formation or in the Discord forum, it's better because all the community is on the Discord forum,

so it's all for this video.

In the next video, we're going to begin new things in this chapter like creation of different datasets.