We are at a time where the algorithms write the code that improves the algorithm.
A Quick Refresher
Before we dig in further, let’s take a moment to go over what we’ve covered so far. Remember when we started? We identified particular problems, a combination of inputs and outputs, and we gave them to what we called a training algorithm. This algorithm will then evolve into a model, which is a handy tool that can take on tasks like sorting or predicting. It just needs a set of inputs to make predictions. That’s machine learning in a nutshell.
What’s cool about this is the way it can adapt to loads of tasks that we come across in our daily life. Imagine being able to predict if someone’s going to fail to pay back a loan, or if ...
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