Read together
Come gather round young ones,
Let me tell you a tale,
Of classifiers and boundaries,
And algorithms that prevail.
There's a method called bagging,
Where samples are combined,
And a classifier is trained,
To make accurate design.
But sometimes there's a bias,
And accuracy can sway,
So another method called boosting,
Helps correct it in its way.
Bayes is a fancy word,
For a probability guess,
It helps find the centroid,
And keeps the model progress.
We talk of classes and boundaries,
To keep things all in line,
And a batch of data to train on,
Makes accuracy just fine.
So there you have it little ones,
A glimpse of what we do,
To make our models perfect,
And our predictions true.
Talk about it
Reflection
- What is machine learning and why is it important?
- Can you name some of the techniques and concepts introduced in the poem?
- How might machine learning be used in real-world situations?
- Can you think of a problem that you would like a computer to help solve?
- Do you think machine learning can be biased? Why or why not?
- What other areas of science and technology do you find interesting?