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Deep Learning with PyTorch: A 60 Minute Blitz [video]

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11–20 of 62 posts

Re: Deep Learning with PyTorch: A 60 Minute Blitz [video]

#12

Very good that Pytorch emerged as a serious contender to TF. While TF still provided more production grade tools (TFX, TensorRT, TF serving), Pytorch continue to evolve and hope soon we have a more complete ecosystem

I really like JAX as well: https://github.com/google/jax. It's younger than PyTorch and TF, but feels cleaner and more expressive. It has a very nice autodiff implementation (based on https://github.com/HIPS/autograd) and performance is comparable to TF in my experience.

Re: Deep Learning with PyTorch: A 60 Minute Blitz [video]

#13

Does no one build their own ml algos anymore? I don't understand the need for pytorch and tensor flow. I honestly thought tensor flow was nothing but a teaching thing for undergrads

Why would you write your own AutoDiff if you do not have to?

Re: Deep Learning with PyTorch: A 60 Minute Blitz [video]

#14

Does no one build their own ml algos anymore? I don't understand the need for pytorch and tensor flow. I honestly thought tensor flow was nothing but a teaching thing for undergrads

This type of reasoning can be extended to any high-level tool. " Does no one writes there own OS. I don't understand the need for Linux or windows. I honestly thought windows or linux was nothing but a tool for undergrads to use Excel or host a WordPress site". And this is not a caricature of your argument. There is a lot of stuff under the hood that Tensorflow or Pytorch implement for a programmer. So much so that people have written wrapper for using TF or Pytorch to even further abstract the working of the library. Implementing deeplearning architecture is less of a science and more of a "let me try this or that" and iterating ideas quickly if of the utmost importance. Also, I can implement a neural network in C (CUDA) although not the auto diff part, but I could if given time to research) but if I started implementing my own library, it would take an order (or even more) of magnitude more time to do the stuff I do daily. We don't need to reinvent the wheel here guys.

Re: Deep Learning with PyTorch: A 60 Minute Blitz [video]

#16

Does no one build their own ml algos anymore? I don't understand the need for pytorch and tensor flow. I honestly thought tensor flow was nothing but a teaching thing for undergrads

I can actually speak to this because I was involved with maintenance on a consultant's neural net built in raw java.

What I have to say is this: please don't build your own.

Re: Deep Learning with PyTorch: A 60 Minute Blitz [video]

#17
post #14

Does no one build their own ml algos anymore? I don't understand the need for pytorch and tensor flow. I honestly thought tensor flow was nothing but a teaching thing for undergrads

This type of reasoning can be extended to any high-level tool. " Does no one writes there own OS. I don't understand the need for Linux or windows. I honestly thought windows or linux was nothing but a tool for undergrads to use Excel or host a WordPress site". And this is not a caricature of your argument. There is a lot of stuff under the hood that Tensorflow or Pytorch implement for a programmer. So much so that p…

That's what I'm getting at, the stuff under the hood is what's important, devil in the details and all that. I'm also a quant so every ml algo needs to be tailored so idk

Re: Deep Learning with PyTorch: A 60 Minute Blitz [video]

#18

Does no one build their own ml algos anymore? I don't understand the need for pytorch and tensor flow. I honestly thought tensor flow was nothing but a teaching thing for undergrads

can we see some of the "ml algos" you've built? in particular your autodiff engine

Re: Deep Learning with PyTorch: A 60 Minute Blitz [video]

#19
post #5

Does no one build their own ml algos anymore? I don't understand the need for pytorch and tensor flow. I honestly thought tensor flow was nothing but a teaching thing for undergrads

Not all of us need to build their own ML algos. Just in the same way that not all of us need to build their sorting libraries or data structures. Some people are specialized in this to develop and do research. While other software engineers just want something they can use without much hassle and just a superficial understanding.

And another reason is standardization. It's a lot easier to use or tweak any given network if it is implemented in the same framework.

Re: Deep Learning with PyTorch: A 60 Minute Blitz [video]

#20
post #8

Earlier quoted context omitted.

Do you write your own crypto libraries too?

>Do you write your own crypto libraries too? Some people do. It's a good challenge.[0] [0] https://cryptopals.com/

But the OP clearly didn't ask about doing it as a challenge or to understand how it works (which is what cryptopals is about), but actual usage.
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