Smerity

26 ms·

181.
by Smerity 11y ago
I disagree strongly. This is the same difference as Linux vs Minix. Minix didn't want anything added as it was said to be for educational purposes even though that didn't reflect the use cases. The author points out that whilst th
182.
Dead Code Should Be Buried – Why I Didn't Contribute to NLTK(spacy.io)
140 points by Smerity 11y ago|62 comments
183.
by Smerity 11y ago
I love your visualizations of the NYC Taxi dataset, minimaxir =] I was just going to mention that if people were interested in exploring this type of data, there exists a Kaggle competition[1] for "Taxi Trajectory Prediction". The
184.
by Smerity 11y ago
Whilst the theory behind the mathematics is clear, it's not necessarily clear it should work well in practice. The weights are initialized as noise, the optimization problem isn't convex so there are numerous local optima to get s
185.
by Smerity 11y ago
If people are interested in getting started with question answering on the bAbi dataset, I wrote a baseline RNN example that's now in Keras[1]. Whilst I love the theory behind the bAbi dataset, there are issues with the data itself tha
186.
by Smerity 11y ago
I like the idea, especially as "content-length" and "content-type" should indicate the likely size and quality of the image. Given that, even the simplest things become problematic when we're downloading millions or
187.
by Smerity 11y ago
If anyone is interested in NLP and hasn't had the chance to use spaCy yet, give it a go now - it's just two commands: "pip install spacy" and "python -m spacy.en.download" =] spaCy is perfect for web-scale NLP
188.
by Smerity 11y ago
Agreed re: the quality of Frank McSherry's posts - they're all great fun and push the technical envelope! I'm glad you brought up Hilbert ordering. It's fascinating but I rarely see it. I usually see Z-order curves in th
189.
by Smerity 11y ago
Other posters have replied giving a back of the envelope as to feasibility, so from the other end: The PageRank implementation on Dato's GraphLab Create when run on the Web Data Commons Hyperlink Graph (128 billion edges) does 3 billio
190.
by Smerity 11y ago
If anyone is interested in graph processing at scale, the largest Web Data Commons Hyperlink Graph[1] (created from Common Crawl[2] data) is 3.5 billion web pages and 128 billion hyperlinks. To my knowledge, it's the largest freely ava
191.
by Smerity 11y ago
Minor note for anyone wanting to re-run all the experiments, there's a one line change that needs to be done such that it will run on QA19[1]. I'll be pushing the updated code to Keras mainline soon. Otherwise, all experiments run
192.
by Smerity 11y ago
I'm certain there are more recent statistics but Google's "Failure Trends in a Large Disk Drive Population"[1] (2007) is a good start: "In addition to presenting failure statistics, we analyze the correlation betwee
193.
by Smerity 11y ago
Thank you for bringing up Mihai Pătraşcu :) I lightly hinted users towards succinct data structures in the article. His work was exactly the type I meant for people to explore - searches for the extreme lower bounds in computer science! I a
194.
How Google Sparsehash achieves two bits of overhead per entry using sparsetable(smerity.com)
54 points by Smerity 11y ago|23 comments
195.
by Smerity 11y ago
One of the most telling points is from /u/imakuram, moderator for /r/books: "This seems to be a seriously stupid decision. We have several AMAs upcoming in /r/books and have no idea how to contact the auth
196.
by Smerity 11y ago
Does anyone know of a modern, comprehensive list of such industrial espionage events from a trustworthy source? One of my go-tos was the European Parliament's report on the ECHELON interception system[1] as it gives an idea of how long
197.
by Smerity 11y ago
It is indeed - I'd suggest the title is modified to add year as it provides context for how long LSTMs have been established before their recent popularity boom. https://scholar.google.com/scholar?hl=en&q=A+First+Lo
198.
by Smerity 11y ago
I disagree with the "big data" line in the sand being whether "a kid doing a paper run could afford your servers". Using spot instances on AWS, you can have a 100 machine cluster with 1.5TB RAM for only $3 per hour. Wor
199.
by Smerity 11y ago
Biased reply (I'm a data scientist there): Common Crawl[1]. We build and maintain an open repository of web crawl data that can be accessed and analyzed by anyone completely free. [1]: http://commoncrawl.org/
200.
by Smerity 11y ago
Whilst I quite enjoy Go, one annoyance I have is that it seems there is no middle ground between alright performance using pure Go and great performance using Go with assembler. Many other languages allow you, if you contort it, to get good
201.
by Smerity 11y ago
Whilst you are correct that the number of allowed computation steps is limited, LSTMs have still been used with success for such tasks. LSTMs have been used to perform addition with 99% accuracy^ on two 9-digit numbers[1]. The paper even sh
202.
Understanding npm – Visualization of npm packages(unpm.nodesource.com)
3 points by Smerity 11y ago|0 comments
203.
by Smerity 11y ago
I'm uncertain whether you mean the algorithm or the output. The question is interesting to both however. The most common method for producing word vectors, skip-grams with negative sampling, has been shown to be equivalent to implicitl
204.
by Smerity 11y ago
If you're looking for even larger graph datasets, the team at WebDataCommons[1] extracted hyperlink graphs from Common Crawl[2]. They're available at both page and domain levels of granularity. The page level hyperlink graphs are
205.
"lp0 on Fire doesn't reliably indicate whether printer is actually aflame"(en.wikipedia.org)
6 points by Smerity 11y ago|1 comments
206.
by Smerity 11y ago
It terrifies me that even disclosing that you are attempting to understand a patent implies you intend to infringe upon it. It's as close to a thoughtcrime as possible without peeking into our heads. Worst of all, this is only happenin
207.
by Smerity 11y ago
His blog posts are easier to follow and aren't forced to be in the academic format :) http://www.frankmcsherry.org/graph/scalability/cost/2015/01/... http://www.frankmcsherry.org&#x2
208.
by Smerity 11y ago
Karpathy is one of my favourite authors - not only is he deeply involved in technical work (audit the CS231n course for more[1]!), he spends much of his time demystifying the field itself, which is a brilliant way to encourage others to exp
209.
by Smerity 11y ago
It's probably worth extending "Your data fits in RAM" to "Your data doesn't fit in RAM, but it does fit on an SSD". So many problems will still work with quite reasonable performance when using an SSD instead.
210.
by Smerity 11y ago
Absolutely spot on - between FlashGraph and Frank McSherry's COST work, the two have really pushed the envelope on efficient large scale graph analysis. Frank McSherry wrote a "call to arms" for the broader graph community at

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