![]() ![]() Here is an example of how linear algebra can achieve greater speed and simplicity. ![]() It turns complicated problems into simple, intuitive, efficiently calculated problems. It provides structures like vectors and matrices (spreadsheets) to hold these numbers and new rules for how to add, subtract, multiply, and divide them. In the context of deep learning, linear algebra is a mathematical toolbox that offers helpful techniques for manipulating groups of numbers simultaneously. NEW: check out machine learning cheatsheet for more topics. Here is a very basic intro to some of the more common linear algebra operations used in deep learning. ![]() I decided to put together a few wiki pages on these topics to improve my understanding. During Jeremy Howard’s excellent deep learning course I realized I was a little rusty on the prerequisites and my fuzziness was impacting my ability to understand concepts like backpropagation. ![]()
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