logancg

9 ms·

31.
Ask HN: Have you read any good “Cli-Fi” (climate fiction) books?
1 points by logancg 10y ago|5 comments
32.
by logancg 10y ago
Hey guys! Thanks for sharing this. I'm actually in the process of starting something similar. What is your approach to ensuring data security for your clients? That's one of the biggest open questions we're always improving.
33.
by logancg 10y ago
This is an extremely interesting example of how a technological fix can emerge in a difficult situation. Transferable to the US context, too. Thanks!
34.
by logancg 10y ago
During the speech [1], Yann (surprisingly) didn't mention consciousness at all. The focus of this segment was the need to "imagine" the future. The premise is that "common sense" – Yann's big theme of the talk
35.
by logancg 10y ago
Sounds cool. But the website says the topic is "A Trump presidency will be good for America". Which is correct?
36.
by logancg 10y ago
Click on the "web" link under the link above the comment section. You can click on the article from there.
37.
China's Thirteenth Five-Year Plan(en.wikipedia.org)
3 points by logancg 10y ago|1 comments
38.
Think Canada is a progressive paradise? That’s mooseshit(theguardian.com)
20 points by logancg 10y ago|15 comments
39.
by logancg 10y ago
Ideally we'd use nothing besides ourselves, but dice is a good idea.
40.
Ask HN: What's the most amount of entropy two humans can create in 30 seconds?
14 points by logancg 10y ago|9 comments
41.
The Manly Guide to Menstruation(medium.com)
2 points by logancg 10y ago|1 comments
42.
Project Cybersyn(en.wikipedia.org)
1 points by logancg 10y ago|0 comments
43.
by logancg 10y ago
The CEO (one of the co-founders) is 18 years old – and already a prolific entrepreneur.[1] He did a great talk at TechCrunch Battlefield.[2] Impressive work by the Beam team. I'm not a gamer (at all), and even I have way too much fun w
44.
‘I don’t like the idea of capitalism’: Charles Koch, unfiltered(washingtonpost.com)
1 points by logancg 10y ago|0 comments
45.
The Race Between Machine and Man (2016)(nber.org)
4 points by logancg 10y ago|0 comments
46.
LIME: Explaining the predictions of any Machine Learning classifier(github.com)
5 points by logancg 10y ago|1 comments
47.
by logancg 11y ago
I spent some time in Singapore. The startup ecosystem has critical pitfalls and successes. There is a lot of money (Government and private), accessible accelerators, mentors, and business ecosystem support. Taxes are low and registering a b
48.
Wabi-sabi(en.wikipedia.org)
3 points by logancg 11y ago|0 comments
49.
by logancg 11y ago
Try ISLR (for learning/prediction-based stats). Probably the best for someone of your level. Incredibly well written, based around examples, reproducible code. The complex parts – the parts where you need math or abstract concepts – ar