
Deep Learning from Scratch to GPU: CUDA and OpenCL - tosh
https://dragan.rocks/articles/19/Deep-Learning-in-Clojure-From-Scratch-to-GPU-6-CUDA-and-OpenCL
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mark_l_watson
Dragon does rock. Amazing how different processor backends and software stacks
are all supported.

I walked away from using Clojure years ago after I transitioned from a Clojure
loving customer to customers who didn’t use Clojure at all. Whenever I read
something written by Dragan I second guess my decision to give up on Clojure.

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bgorman
This is really a perfect case study of why Clojure is the ultimate language
for a single person's productivity. Macros and JVM access are a huge
productivity increase compared to other functional languages.

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coolreader18
I saw the headline and for a second thought it was about running Scratch
([https://scratch.mit.edu](https://scratch.mit.edu)) on the GPU.

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kumarvvr
Does anyone know any good resources in learning about selection, construction
and evaluation of deep learning network architectures to solve various classes
of problems?

To many articles seem to be about how to use a particular stack or platform
rather than the NN architectures themselves.

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rramadass
You might want to take a look at the books by Timothy Masters. Though i have
not looked at his Deep Learning books, his earlier NN books were full of
practical advice on the various models/architectures and how to map them to
real-world problems.

