Coffee roasting lab: np.tile purpose

[iwanbk]

There is this part in the lab

Tile/copy our data to increase the training set size and reduce the number of training epochs.

Xt = np.tile(Xn,(1000,1))
Yt= np.tile(Y,(1000,1))

Can someone point me to the explanation of this step, why we need to do this?

I’m sure if it is already discussed in the video, but i can’t remember it being discussed.

Googling it doesn’t give me result as well.

Thanks

[saifkhanengr]

This technique is called “data augmentation,” very common in ML. With these additional samples, the model can generalizable patterns more accurately, which can improve its performance.

Best,
Saif,

[iwanbk]

Thanks @saifkhanengr for the reply, very appreciated it!