What exactly is machine learning and how does it work?
In: Technology
ML is a pretty general term, and I’m not sure if there is a formal common denominator that defines whether a particular approach can be described as machine learning, but if we use decision trees as an example as it’s one of the simpler forms.
Say you have some existing data about your basketball team’s matches which is neatly organized by 2 columns: Michael Jordan participated, and win/lose.
You write some function that aims to take the existing data (the training data) and find some correlation: If we only look at the times Michael Jordan participated, the team won 51% of the time. You then insert this value into your model, which is just a term for your math function you wrote with pen and paper or a Python script.
Now you can ask your model: If Michael Jordan participates in a match, how likely are they to win?
This is such an oversimplified example that it’s not useful in itself, but now you can start to expand on the function that takes existing, factual data and tries to find some correlation in the information it will receive in the future to predict an unknown result. How this should be done is what you learn by taking a machine learning class.
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