jph00

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691.
An Introduction to Deep Learning for Tabular Data(kdnuggets.com)
4 points by jph00 8y ago|0 comments
692.
by jph00 8y ago
I'm not sure - what you're describing is information extraction. I haven't tried that yet, but I'm certainly interested in doing so (especially for medical data).
693.
by jph00 8y ago
That would certainly be one of them.
694.
by jph00 8y ago
Very interesting comments. Yes absolutely want to do comparisons to ELMo. It's a little tricky to do so on our datasets, since ELMo isn't really a complete method on its own, but more an addendum to existing methods. In the future
695.
by jph00 8y ago
Of course not. The use of pre-training on a large unlabeled corpus and subsequent fine-tuning is what the paper is about. It is stated repeatedly in the paper and the post. It is totally correct and in no way misleading to say we need onl
696.
by jph00 8y ago
Yes I think it would work great for both of those applications. For readability, you'd ideally want a dataset showing how long someone took to read each document. For entertainment, some kind of review dataset would be fine (it's
697.
by jph00 8y ago
> but in the grand of scheme of things, 1% absolute improvement may not be such game-changer, especially if it comes at the cost of other relevant metrics like model complexity, developer sanity or performance fasttext makes errors about
698.
by jph00 8y ago
It beats it easily. See the paper and citations for comparison
699.
by jph00 8y ago
No I don't know what that is
700.
by jph00 8y ago
Doesn't look like it. Hope to see someone take it up!
701.
by jph00 8y ago
fasttext is just an encoding of the first layer of a model (the word embeddings - or subword embeddings). Full multi-layer pre-trained models are able to do a lot more. For instance, on IMDb sentiment our method is about twice as accurate a
702.
by jph00 8y ago
D'oh! Many thanks - fixed that one too.
703.
by jph00 8y ago
The post mentions that there's work ongoing to make this available in languages other than English. If you'd like to help contribute a language, there's a discussion thread available with 20 languages under development so far
704.
by jph00 8y ago
Oops - forgot the leading '/'. Fixed now. Many thanks for letting us know.
705.
by jph00 8y ago
Jeremy here (co-author of this paper). Let me know if you have any questions!
706.
State-of-the-art text classification with universal language models(nlp.fast.ai)
346 points by jph00 8y ago|51 comments
707.
by jph00 8y ago
Yup potentially. The jury is still out on which will win, or whether both have their place!
708.
by jph00 8y ago
Yup it's multi-layer bidir seq2seq with attention, and a few tricks like teacher forcing. Same as Google Translate. Their version takes a long time to train on a lot of GPUs, so we simplify it by using less layers, and a smaller, simpl
709.
by jph00 8y ago
We're certainly looking for ways to help develop the community. Obviously http://forums.fast.ai is a good starting point, and is a very active and supportive community nowadays. But I'm interested in finding ways to su
710.
by jph00 8y ago
Exactly right - it's all about your portfolio. We spend a lot of time throughout the course talking about ways to build that portfolio, and folks on the forums support each other with feedback and help on these projects. Completing a M
711.
by jph00 8y ago
We're so early in the software and tools cycle for DL that it's unlikely anything that exists today will remain relevant in its current form for very long. You can see that every couple of years the entire DL ecosystem is getting
712.
by jph00 8y ago
> For example, how do you expect to understand how to minimize an utility function if you have no idea of what a gradient is, how you calculate it, and why you want to descend through it. The course teaches all those things - as the comm
713.
by jph00 8y ago
Rachel's mic is always off until I turn it on. So if she's asking a question, it's only after she's visually indicated that she wishes to do so, and I've found a time in my presentation that I'm ready to take i
714.
by jph00 8y ago
Ganguli's papers are at the more "math-y" end of the spectrum when it comes to DL papers. So don't worry if you're finding them a bit unapproachable. In part 2 of the course I provide quite a bit of advice about how
715.
by jph00 8y ago
Thanks for the feedback! One thing you may be interested in, if you haven't seen it, is that you can right-click the video and copy a link to the current time code, so you can always go back to where you were (or just pause the video i
716.
by jph00 8y ago
Top-down vs bottom-up depends to some extent on what you enjoy, vs what you need to be patient about. With our top-down approach you do get to all of the 'why', but only after understanding 'how'. So it's good for
717.
by jph00 8y ago
Dr Rachel Thomas, the co-founder of fast.ai, is the person who takes the highest voted questions from our 600+ in-person students and passes them on to me, as I asked her to do. At least 4 different people must have wanted the question aske
718.
by jph00 8y ago
This linked course is part 2, so this isn't a good starting point. But part 1 is! :) Here's the link: http://course.fast.ai . We assume you're familiar with python and somewhat familiar with numpy. If you're
719.
by jph00 8y ago
I haven't taken the course - and I'm hopelessly biased anyway so you shouldn't trust my comments. However a lot of our students have done it. Here's a couple of their comments (search the linked thread if you want more):
720.
by jph00 8y ago
I might be helping author a textbook based on our upcoming introduction to machine learning MOOC. Which maybe one day would lead to a deep learning book - but that would be years away! (BTW, I used to think I didn't like videos for lea

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