All right, so now we are ready to compile and see if we have any syntax error, and if not, we're
going to start training GOGGOMOBIL so on around here.
Let's see if we have any errors.
And it's complaining that there is nothing called kierra model, OK?
It's called actually Chira models.
There is an S here.
Sorry about that.
Let us try again.
We have another.
It is regarding the shape it is in line eleven.
OK, so the problem is here, we need to add the parentheses at the end because this 2D is the one that
is containing all of these information.
So, of course, we are going to be having the same issue here.
So delete this and close the parentheses correctly.
Now, again, turn it off.
Turn it on again.
Let's see if we have any other issues.
It's totally normal to have some syntax issues when you're writing your code.
So this is why we are trying to work them together.
We are still having one more ball, size is not defined.
Let us check the ball size here.
We need an equal sign.
So it is actually full size equals two to not passing to two to it.
So that's OK.
Let us continue.
OK, let's take a look about the air we are seeing the fire is not defined, OK, because we classify
around over there, here there is another I.
Again, stop, start again.
Let's see if we have any more syntax errors.
It's complaining now about metrics.
There is an additional log here should be metrics.
OK, stop, start again.
It is very important to the Earth in order to know what's going on, always try to read the last one
here involved keyword and compile metrics.
Accuracy is not spelled correctly.
So this is a Cura, see?
OK, so now let's try again.
Image data generator is not defined.
We forgot actually to import it, so let's say from Kiraz that.
Preprocessing.
The Amish import image data generator.
OK, let us try again.
Now, we have another error here in line 30, it says it did not expect that because it's called actually
batch size.
Not bad.
Same thing here we have a batch size one more time.
Fingers crossed.
Let's solve this time.
We don't have any more syntax errors.
This is not defined here, it's got this set, not this test.
Again.
Here we have step approach.
It should be steps and validation steps.
Finally, here we have a poaches was there as well.
Again, an expected keyword argument, validation, this data set, it should be only validation data.
And here we go now we are starting to train our data.
As you can see here, the accuracy is increasing and the lows should be always decreasing.
This is your criteria if your model is learning correctly or not.
So as we can see, losses still dropping.
Now, I'm going to let this run and then we are going to see the final result and we will see if we
need to adjust the and so that we can get any better accuracy or the accuracy is already good and we
don't need to do anything.