Submitted by AutoModerator t3_110j0cp in MachineLearning
TheGamingPhoenix_000 t1_j8p1o9l wrote
Dumb Question: Where is a good resource to understand the actual math going on, most resources I find with a simple google search is only api usage, not actually what all the parameters and such mean
[deleted] t1_j8zl1hb wrote
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TheGamingPhoenix_000 t1_j921z2o wrote
That just explains the api usage tho, not the actual reasoning and how they do the math. Like on section 5, they create a model but don’t actually explain the parameters they use. Like why do they use a dense layer instead of something else, why do they use the adam optimizer, etc.
I don’t understand what all the terms mean, dense, lstm, optimizers, and stuff, I want to find out what these all mean and when to use then
[deleted] t1_j923mho wrote
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ParanoidTire t1_j9hd4r5 wrote
Welcome to the world of research. You can find all that stuff in so called "papers", i.e. publications. To get started I would suggest to have a look at one of the most influential architectures: resnet. Just Google "resnet paper" and your good to go (too lazy to fetch the citation, but it's by he et al.)
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