2019
HN on the spotlight: Spotify to Apple and Google and DuckDuckGo.
Exactement, comme dans une épicerie. Et il faut voir ce que cela donne avec le
bétail dedans… #fr
MacJournal 7 is now free. I will stay by Org for managing my text files, but it’s good to know anyway. (via Jack Baty)
Here is the best take I found on imperative vs. functionnal approach using Lisp. #lisp
TIL Better to use partition rather than split when you want to convert a ‘string’ to a ‘dict’ based on the first occurence of a specific delimiter (as in .split(..., 1)). Note that unlike split, the delimiter is kept and you probably don’t want to keep it. #python
Mathematical Recreations and Essays, by W. W. Rouse Ball. (Note that the PDF is nicely hyper-linked!)
Another common trick is to throw twenty cards on to a table in ten couples, and ask someone to select one couple. The cards are then taken up, and dealt out in a certain manner into four rows each containing five cards. If the rows which contain the given cards are indicated, the cards selected are known at once.
The value of owning more books than you can read. I have thousands of books in my home, many of which are more than 20 years old. From time to time it seems to me that’s all I have left. I’ve read them all except the last ones I bought. However, I can understand what it’s like to contemplate all that we still have to learn.
TIL. There’s a nice option when you edit Python code under Emacs which consists in sorting automagically all import statement. In most cases, it works great, however there are some edge cases. E.g., it is common in Flask applications to have import defined after initializing the app itself, because of cicular imports. Hopefully, it is possible to override the default settings and to add a local directory variable, as recommended on Spacemacs website (SPC f v d). #emacs
Sadly, there’s not such a steady flow on Pragmatic Emacs. #emacs
I wish I had read this nice post on Travis-CI, by Julia Silge, before I struggle
myself with Travis and R. Unrelated but also interesting post: Tensorflow, Jane
Austen, and Text Generation. #rstats
Understanding how text generation works with deep learning and TensorFlow has been very helpful for me as I wrap my brain around these techniques more broadly. And that’s good, because exactly how practical of a skill is this, right?! I mean, who needs to generate new text from an existing corpus in their day job?
I forgot about OSF. Here is a nice read: A chill intro to causal inference via propensity scores. Not only do we have a 16 page-long PDF, but also the accompagnying source files! (via @george_berry)
Generating Uniformly Random points on a d-sphere and d-ball. (via @Atabey_Kaygun)
📖 Rezvani, Le magicien (Actes Sud, 2006)
Clearly, I’m not that active in the early afternoon. Either because of the lunch break or the half-life of my medication… Anyway, Timing is the best time tracking app I’ve seen in a while.
I’m in my third year with the 12-inch Macbook (generously offered by SB). It is certainly the best laptop I got in 13 years. Sometimes I feel like I miss the tiny pulsing light (aka sleep indicator) that we used to have on older metallic aluminum body ones. Well, we have backlit keyboard now, even if it is like a butterfly keyboard ;-)
7 Unix Commands Every Data Scientist Should Know. I lost track of the number of blog posts I read where the title includes “un*x commands that (data) scientists should know.” I expect that soon or later mastering deep learning techniques will be a mandatory skill as well. Anyway, this gentle tutorial is well tied up, so go read it if you want to refresh your memory.
So it seems that we will be done with The Expanse, Season 1, tonight.
Nice. I spent some time checking Dimitri Fontaine’s Github repo, in particular his advent of code in Common Lisp. I am currently reading his book on PostgreSQL, but I couldn’t resist reading some Lisp code after lunch.
Exterminate Magit buffers: Quite useful tip if like me you happen to kill your
Magit buffers by hand. #emacs
Viewing Matrices & Probability as Graphs. With great illustrations. For those
interested in catgeory theory, the other posts are worth a look too. See, e.g.
this booklet on arXiv (PDF, 50 pp.). #maths
Rash - The Reckless Racket Shell. (via @NlightNFotis) #scheme
Natural Gradient Descent. Be sure to check the rest of the site. I just added it to my RSS reader.
Vim within Emacs: A very good read even if you’re not versed into Spacemacs.
#emacs
Better than time? gnomon is a command line utility to prepend timestamp
information to the standard output of another command.
As I am using Postgresql a lot these days, I thought I would import a large CSV
file (1 Go) to see if I can play with in-database tools from dplyr & Co. I will
probably need this for work so it’s worth the effort. I started with a Stata
file that I read using haven, and I converted it to a CSV using
data.table::fwrite. This already eated up all my RAM. Now, I’m using csvkit to
import the CSV file into a Postgresql local database. Well, it says a lot about
the process:
I guess I just found another org-powered user! #emacs
Just added to my Papers list: Mean and median bias reduction in generalized
linear models. See also the brglm2 R package. #rstats
I haven’t written a single line of Latex in a long time, but it looks like we now get Font Awesome for free in our TeX distribution. (via @kaz_yos)
It’s astonishing how much work has been done regarding working with database
using R. We now have dbplot and modeldb (not to be confused with this one). (via
@theotheredgar) #rstats
syn uses OS X’s natural language processing tools to tokenize and highlight
text. Nice utility to add to my writing stack. It is used by Emacs
wordsmith-mode. #emacs
Okay, so it looks like we started with season 2 of The Expanse instead of season 1. Great! That may well explain why we didn’t understand anything during the first episodes.
Prompted by a recent Twitter question, I was about to benchmark some R packages
to process large files. However, there already seems to be a very nice post
about this: Working with pretty big data in R. #rstats
Today was my first attempt at building a Flask site, using a boilerplate Bootstrap theme, and a Postgresql backend. Done. On reflection, I wonder why I continue to maintain PHP websites.
Principles and Techniques of Data Science. Nice ressource to have! It’s been
written using Jupyter book, btw. #python
This Elisp cheatsheet (PDF) is really great. #emacs
Anatomy of a logistic growth curve, by Tristan Mahr. Nice looking visualization
and clearly a non mathy but well put explanation of the logistic curve. I wish I
read this earlier, when I started teaching psychometrics. #rstats
Immersive Linear Algebra. #maths
Trying out Travis CI for a Bookdown project. I’m already at the third failure
and it starts to be painful. #rstats
Linear algebra in Emacs using MKL and dynamic modules. #emacs