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The ability to understand mathematical processes is widespread, but the ability to parse mathematical notation isn't. Insisting on teaching deep learning (which is fundamentally software engineering, not mathematics) with equations is like insisting on teaching Hegel in German.
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I just got done reading
@Sentdex book neural networks from scratch and I think it did a really good job of making that connectionThanks. Twitter will use this to make your timeline better. UndoUndo
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Probably my inexperience but I feel like math notation also has a lot of implied steps that are actually missing from notation. My number one problem with it. Once i see the code it's sooo much clearer. Another problem is the different writing conventions...
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This is why your book was so fantastic. Like, I appreciate *some* theory, but it's so much more fun to learn hands-on.
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Agree. I guess people use math notations to secure a sense of superiority...
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Math notation is invented to concisely represent ideas. It's intended to make your life easier, not harder. Of course there's a barrier to entry with learning the notation, but it has nothing to do wirh superiority and everything to do with convenience
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The fact that so many people can do Deep learning without worrying about the underlying math is a testimony to the maturity of the technology, including all associated libraries.
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I learned during an intern and with CS231n, but mostly through programming exercises. I had no previous courses about it, but I know that the math part at my uni would have discouraged me a lot.
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You ok? Aerospace engineering is engineering and not mathematics, so by your logic we should omit equations from it.
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