paulfharrison

6 ms·

1.
by paulfharrison 1mo ago
Nice. This is close enough to an R level of brevity, without any R dark magic. Would be a great addition to the cheatsheet.
2.
by paulfharrison 1mo ago
I'm sure Polars is great, but I can't get over needing 10 characters of ceremony every time I want to refer to a column in a data frame. pl.col("...")
3.
by paulfharrison 1mo ago
A comment by Norbert Wiener on translation machines (published 1993 but written somewhat earlier in "Invention: The Care and Feeding of Ideas"): "Thus the effect of the machine of this sort in intellectual work may be to decr
4.
by paulfharrison 4mo ago
It's nice to see sparse interpretable LLMs being made. This is similar to factor rotation in factor analysis (or PCA). A varimax rotation, for example, can produce an equivalent factor analysis with sparse loadings, and which is genera
5.
by paulfharrison 5mo ago
This advice can also be applied to PhD thesis examinations and paper reviews.
6.
by paulfharrison 5mo ago
My dad is in his 80s. He keeps careful notes on how to use devices like tablets and TVs. There might be a touch of engineer-brain at work here, but the struggle is very real. He generally wouldn't take in all of the text and symbols on
7.
by paulfharrison 9mo ago
For linear models, least squares leads to the BLUE estimator: Best Linear Unbiassed Estimator. This acronym is doing a lot of work with each of the words having a specific technical meaning. Fitting the model is also "nice" mathem
8.
by paulfharrison 9mo ago
A note mostly about terminology: The least squares model will produce unbiassed predictions of y given x, i.e. predictions for which the average error is zero. This is the usual technical definition of unbiassed in statistics, but may not c
9.
by paulfharrison 10mo ago
535.491…^i = 1
10.
by paulfharrison 10mo ago
R is so good in part because of the efforts of people like Di Cook, Hadley Wickham, and Yihui Xie to create an software environment that they like working in. It also helps that in R any function can completely change how its arguments are
11.
by paulfharrison 11mo ago
Producing a diverse list of results may still help in a couple of ways here. * If there are a lot of lexical matches, real semantic matches may still be in the list but far down the list. A diverse set of, say, 20 results may have a better
12.
by paulfharrison 1y ago
Here's a scenario. You're running a cluster, and your users are biologists producing large datasets. They need to run some very specific command line software to assemble genomes. They need to edit SLURM scripts over SSH. This is
13.
by paulfharrison 1y ago
What a strange web page. Scrolling is thoroughly broken. I recently went to a two day workshop on whole cell modelling. I'm still trying to work out how much of the exercise is fantasy. I get that some of the chemistry is well enough u
14.
by paulfharrison 2y ago
Thanks for this. Despite the vintage this seems very clearly written, the introductory material on measure theory has already made it worthwhile for me.
15.
by paulfharrison 2y ago
As others have said in various ways, start by fitting a survival model using glmnet. That said, here are some folks trying to use SDEs to model cells, they even have a "dW" on their logo. This is a long way from predicting age of
16.
by paulfharrison 2y ago
A further step is Langevin Dynamics, where the system has damped momentum, and the noise is inserted into the momentum. This can be used in molecular dynamics simulations, and it can also be used for Bayesian MCMC sampling. Oddly, most ment
17.
by paulfharrison 2y ago
It could also be that the aspect of personality that causes people to think Kagi is better also causes those people to buy it.
18.
by paulfharrison 2y ago
Brownian motion mentioned at the end of the article and more generally Langevin Dynamics are incredibly useful. They're this weird interface between normal physics and statistical mechanics. When a big complex molecule is constantly jo
19.
by paulfharrison 2y ago
If you plot x^y against x+y, you get a Sierpinski triangle.
20.
by paulfharrison 2y ago
The article mentions equivalent ranking from cosine similarity and Euclidean distance. The derivation is very simple. For vectors A and B, the squared Euclidean distance is: (A-B).(A-B) = A.A-2A.B+B.B A and B only interact through a dot pro
21.
by paulfharrison 2y ago
For web-servers on remote machines, I have found this useful: socat TCP4-LISTEN:1234,fork,bind=127.0.0.1 EXEC:'ssh my.remote.server nc 127.0.0.1 1234' 1234 = local/remote port. Can be adapted to use unix sockets at the