From the course: Data Science Foundations: Fundamentals

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Algebra

Algebra

- [Instructor] When you're working with data, it's not too hard to come up with a solution when you have only one problem at a time, and it's basically stationary. But it's a whole different story when you have thousands of problems stampeding at you at the same time, in that case, you need a more flexible approach, and this is where algebra can come to the rescue. There are two reasons that it's important to understand algebra and data science, number one is that it allows you to scale up. The solution you create to a problem should deal efficiently with many instances at once, basically create it once, run it many times. And the other one closely related to that is the ability to generalize. Your solutions should not apply to just a few specific cases with what's called magic numbers, but to cases that vary in a wide range of arbitrary ways, so you want to prepare for as many contingencies as possible. And so we'll…

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