williamtrask

38 ms·

451.
by williamtrask 11y ago
Generally, the industry benchmarks dependency parsing using gold standard POS tags. However, your point is well taken. Personally, I have little doubt that it would still yield the same level of improvement, but fortunately a bit of experim
452.
by williamtrask 11y ago
Perhaps, but seeing as POS taggers are ~97% accurate (at least in English), I'd expect this to be minimal. Furthermore, the baseline neural network also has access to the gold standard POS tags, so the comparison of adding POS disambig
453.
by williamtrask 11y ago
Great point. In my opinion, for improving the quality of syntactic tasks such as POS / dependency parse, the difference between disambiguating and not disambiguating riverbank and financial bank will be minimal. However, for semantic t
454.
by williamtrask 11y ago
In this case, there is no performance tradeoff except that of running your core NLP pipeline... for which there are several very fast options
455.
by williamtrask 11y ago
working on it. we'll see.
456.
Sense2vec – A Fast and Accurate Method for Word Sense Disambiguation(arxiv.org)
131 points by williamtrask 11y ago|41 comments
457.
by williamtrask 11y ago
Glad you liked it! For the gifs... http://makeagif.com/
458.
by williamtrask 11y ago
excellent post
459.
by williamtrask 11y ago
not sure what happened...should be back up now. I'm guessing github hiccup
460.
Anyone Can Learn to Code an LSTM-RNN (Part 1: RNN)(iamtrask.github.io)
125 points by williamtrask 11y ago|14 comments
461.
by williamtrask 11y ago
how does this have 420 points after 8 hours...yet is on the 4th page?
462.
Crazy Awesome Deep Learning Data Science (Skip to Minute 23)(exponential.singularityu.org)
2 points by williamtrask 11y ago|0 comments
463.
Using Windows 10? Microsoft is watching(newsweek.com)
56 points by williamtrask 11y ago|75 comments
464.
The Magic of RPython(kirbyfan64.github.io)
86 points by williamtrask 11y ago|20 comments
465.
Part 3: Adding Dropout In Python Neural Network(iamtrask.github.io)
2 points by williamtrask 11y ago|0 comments
466.
TUTORIAL: Gradient Descent in 13 Lines of Python(iamtrask.github.io)
2 points by williamtrask 11y ago|0 comments
467.
A neural network in 13 lines of python (Part 2 - Stochastic Gradient Descent)(iamtrask.github.io)
17 points by williamtrask 11y ago|0 comments
468.
by williamtrask 11y ago
Hey avyfain, I'll look out for that in my next post. Thanks for the note.
469.
Beginner Tutorial: A Neural Network in 11 Lines of Python (or Less)(iamtrask.github.io)
2 points by williamtrask 11y ago|0 comments
470.
ICML 2015: New SOA for Neural Word Embeddings by Modeling Word and Char Order(arxiv.org)
1 points by williamtrask 11y ago|0 comments