shazeline

It was gusting at 33kts.

33kt/hr * 1.15mi/kt * 1.609km/mi ~= 61km/hr.

The weather app was right. Just different units.

There was an interesting problem about qanats and excavation cost minimization in the 2015 ICPC World Finals problem set.

(Problem H) https://icpc.baylor.edu/worldfinals/problems/icpc2015.pdf

You can probably get away with undergraduate degree graduation year as a rough proxy for age.

age(grad_year) ~= (2016 - grad_year) + 22

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You generally don't know if you've reached a suitable maxima, which is why it is good to run a nondeterministic optimizer a few times (if computation power allows) and see if there are any reliable parameters form there.

There are also somewhat better-than-random strategies such as Bayesian optimization and particle swarm optimization that can help you to search more efficiently.

Cool! I think this project is really awesome and your blog is full of interesting things. Keep up the great work!

Is there any way to set tcpKeepAlive=true, ssl=true, and specify a sslrootcert (for Redshift use)?

CART forms the basis of the decision trees used by scikit-learn's implementation of random forests [1]. CART may be old, but definitely not outdated.

[1] https://github.com/scikit-learn/scikit-learn/blob/master/skl...

I would argue that an increase in ride-sharing usage reduces traffic congestion.

You're right. But it's already known that the actual dress is "blue and black" as someone found it on amazon. It's essentially the picture that is creating the ambiguity.

I did some basic color analysis here.

http://shahidchohan.com/resolving-the-dress-color-debate/

I skimmed the source and didn't see anything regarding leader election. Am I missing something or is this implementation encapsulating some of the underlying terminology/analogies traditionally used by Raft?

One common approach is to look for the elbow in the curve <metric> vs K (number of clusters). This is essentially finding the number of clusters after which the rate of information gained/variance explained/<metric> slows. I believe it's possible to binary search for this point if you can assume the curve is convex.

Current UCLA student. I just sent a request. Waiting to see what happens.

I think it is more accurate to say that data science isn't Kaggle. The process of taking a data set and fitting it to the most robust model is certainly machine learning.

I wrote a quick script to generate a list similar to (but not as deep or well-annotated as) Prof Palsberg's.

https://gist.github.com/shazeline/d9881d06be31a59a93d3

It's a BFS for Google Scholar seeded with Herbert Simon.

postmaster

Yeah, trg2 would need to put all the edge case rules towards the beginning. That, or just put the basic rules at the beginning and have separate conditionals at the end to handle the edge cases.