jph00

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631.
by jph00 8y ago
The pointer approach allows for brevity and idiomatic swift at the place of use. The verbosity behind the scenes need not bother the user. Because I couldn't find anything that provides that using the approach you are discussing, I did
632.
by jph00 8y ago
What I'm doing is essentially the same as `withUnsafeMutableBufferPointer`. However I didn't find a way to get concise abstractions using that approach.
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by jph00 8y ago
Flux.jl does look terrific. Frankly, part of my interest in this little Swift research project was to pick something that's not at all well explored, and try to dig in to it. Julia is much more mature for machine learning than Swift at
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by jph00 8y ago
That sounds totally fair. I haven't used Julia for a couple of years so my comments on it are dated and not well informed. Everyone I know that uses Julia nowadays loves it.
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by jph00 8y ago
Hello folks! I wrote this article - so if you have any questions, feel free to shoot them my way. :)
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by jph00 8y ago
My favorite is ULMFiT, although to be fair I'm an author on that paper... ;) Frankly, all these papers are pretty great. But perhaps the most impressive results are BigGAN (amazing image generation) and BERT (doing things with NLP that
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by jph00 8y ago
A new version for PyTorch v1 will be released next month, FYI.
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Finally, a Machine That Can Finish Your Sentence(nytimes.com)
2 points by jph00 8y ago|0 comments
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by jph00 8y ago
Can you be specific? fast.ai has no revenue at all, no investment dollars at all, no marketing team, and no PR budget. It's entirely self-funded out of my pocket personally in order to help people. The courses are all free, there are n
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by jph00 8y ago
We also have made all of these datasets available as torrents, particularly to support Chinese practitioners and other places with connection issues. Thanks to Max Pechyonkin for helping with this. http://academictorrents.com&#x2
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by jph00 8y ago
Thanks! Now it's set up it's easy for me to add more datasets, or make changes, so feedback is most welcome.
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by jph00 8y ago
There's a development notebook for segmentation on the Carvana dataset. https://github.com/fastai/fastai_docs/blob/master/dev_nb/006... Most of the functions in there are pre defined in fastai
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by jph00 8y ago
ZDNet just published an article with some more background about this BTW : https://www.zdnet.com/google-amp/article/fast-ais-new-softwa...
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by jph00 8y ago
1. Less boilerplate, so you can focus on your algorithm; best practices built in, so you might be surprised at how your speed and accuracy may improve 2. Very close integration with PyTorch. fastai is designed to extend PyTorch, not hide
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by jph00 8y ago
The story on python is much better nowadays. You can install cuda and drivers from nvidia, and then install anaconda, then just run: conda install -c pytorch -c fastai fastai pytorch-nightly cuda92 If you don't use conda, thin
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by jph00 8y ago
Keras doesn't support PyTorch, so it's not exactly an alternative. But it would be fair to call it an inspiration for fastai.
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by jph00 8y ago
It's very fast indeed: http://www.fast.ai/2018/08/10/fastai-diu-imagenet/ For inference, new features being announced today at the conference will help a lot too.
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by jph00 8y ago
It supports segmentation right now, but object detection won't be supported "out of the box" until 1.1 (in a month or two). You can certainly train a YOLO or SSD pytorch model with fastai, however.
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by jph00 8y ago
I assume they are referring to the TWiMLAI podcast that was posted this morning https://twimlai.com/twiml-talk-186-the-fastai-v1-deep-learni...
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by jph00 8y ago
None of fastai is backwards compatible with v0.7 - although the API has a similar structure, so it shouldn't be hard to rewrite. PyTorch v1.0 also has some big differences to the version we used in the course. I suggest you create a ne
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by jph00 8y ago
There used to be a terrific company called FlightCaster that did exactly this. They had a mobile app that would tell you much more reliably than airlines when your flight was likely to depart. It was fantastic for getting ahead of the queue
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by jph00 8y ago
@pesenti, it's still looking grey and very thin font on my computer - quite hard to read. Especially with the grey background for the code. I did a full refresh.
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by jph00 8y ago
MacOS is really hard to work with for deep learning. Try https://salamander.ai/ . $0.19/hour for a server with NVIDIA GPU, fastai v1 pre-installed with notebooks and datasets. Or try Google Cloud preemptible instances
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by jph00 8y ago
They're not built in yet. Still suggested to compile from source. I'm not sure if it supports PyTorch 1.0 yet. More info: https://pytorch.org/blog/tensor-comprehensions/
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by jph00 8y ago
From https://news.ycombinator.com/newsguidelines.html : " Please don't impute astroturfing or shillage. That degrades discussion and is usually mistaken. If you're worried about it, email us and we'll lo
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by jph00 8y ago
I think PyTorch is still ahead of Tensorflow for interactive coding. But the next version of Tensorflow (2.0) looks like it could be a lot better, so there's a chance we'll add support for that later. No promises though!...
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by jph00 8y ago
Jeremy from fast.ai here - I'm sitting here at the PyTorch developer conference, listening to all the really great new stuff being announced. :) Happy to answer any questions about the fastai library release here. It's a rewrite f
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by jph00 8y ago
PyTorch 1.0 is just fantastic. A shameless plug: we (fast.ai) are also releasing fastai 1.0 for PyTorch today. fastai makes a lot of stuff in PyTorch easier to use, whilst allowing full customization with PyTorch code. http://www
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by jph00 8y ago
Fixed now, thanks :)
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by jph00 8y ago
The biggest difference is that Andrew's teaching style tends to be more bottom-up and math-first, whereas mine is top-down and code-first. They both should give you a thorough foundation if you complete the course. Why not watch the fi

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