Welcome back.
Did you see how important to visualize data like.
Actual and predicted data.
Also how to make this graph.
So Matplot library is a very important library.
I advise you to use it in many, uh, in many fields and in many projects in order to understand well
your data, understand your model, understand your results and so on.
Another metrics and results we can observe and display and visualize using matplotlib is the plot,
training histories and the errors.
So here we are plotting errors and loss.
And a loss means the MSE.
Let's start with plot.
So whenever you want to create a new graph plot dot figure figure size ten by four plot subplot 1 to
1.
Plot history.
Loss.
Title.
Model loss.
label, last MC and label epic.
Everything we've seen in the previous videos except the plot dot subplot.
This creates a one row, two column grid of subplots and selects the first subplot, which is the left
side.
Let me run and here we go.
We have the epic from 0 to 1000 and from 0 to 25.
The loss in MSE.
And you notice that the loss in MSE decreased sharply to roughly around zero and continue this straight
line.
So this is the last MSE.
So as as you train your model as the result becomes better.
Let me display the Mae.
So plot subplot.
We have to the right here and the same as before.
The subplot creates one row two column and to select the right side and plot.
History.
History and model.
May and X label.
The epic Y label is May run.
And here we go.
We have the model loss and the model.
May you see guys, the model may starts from five degrees to roughly around 0.5 and then decreased around
to 0.2.
Okay.
You see guys the model and the model loss.
Every epoch gets better.
So 1000 epoch 1000 epochs gets better and better.
Um results better trained, model loss decreased and the errors decreased.
Okay.
So this is how we analyze the model loss MSE and Mae and plot them onto those graphs.