
Introduction to Recurrent Neural Networks in Pytorch - cpuheater
https://www.cpuheater.com/deep-learning/introduction-to-recurrent-neural-networks-in-pytorch/
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TheAnig
Sound like a pretty neat introduction! This is exactly the kind of thing I
needed, coming from tf/keras and looking to switch to pytorch for research

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Larrikin
As someone learning Keras right now, why are you wanting too switch?

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chrisfosterelli
Not the parent, but the imperative interface supported by the dynamic graph
approach Pytorch takes is much nicer.

Additionally, in my personal opinion Tensorflow is often too low level and
Keras is often too high level for the things I'm trying to do for research.
While you can jump between the two of course, I think PyTorch hits a much more
natural middle ground in its API.

Tensorflow/Keras is making improvements in these areas with the eager
execution, and is still great for putting models into production, but I think
PyTorch is much better for doing research or toying with new concepts.

This article has some good comparison:
[http://www.goldsborough.me/ml/ai/python/2018/02/04/20-17-20-...](http://www.goldsborough.me/ml/ai/python/2018/02/04/20-17-20-a_promenade_of_pytorch/)

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WhitneyLand
I assume this is more intro to Pytorch than intro to ML.

Any tips on an high quality intro to ML content using PyTorch for the hands on
examples?

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nl
The Fast.ai courses are great.

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pugio
Seconded. Their courses are superb, and they have their own library built on
top of PyTorch that makes creating high quality models even easier.

You start with their lib, and over time they teach you all the techniques
they're using, so the easy black box you start with becomes more transparent
over time. It's a hands-on, code-first approach.

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nl
This is an interesting introduction to writing your own neural network models
from scratch in PyTorch.

I don't think it's a great way to learn it though - almost no one writes their
own models from scratch.

Almost all the time you want to be using one of the pre-written RNN models,
since they are optimized, debugged and do things like use CuDNN where
available.

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erezsh
I'm not sure what's the point. Predicting the sine-wave is pretty trivial with
NN, and doesn't require a RNN.

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sarabande
It's an educational post. Calling something "pretty trivial" doesn't reduce
the value of the post for people who don't know what you know, and want to
learn it.

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erezsh
That wasn't my point. How can a post teach recurrent networks, if the
"recurrent" part of it is redundant, and the network would work perfectly well
without it?

