Pretty Magit - Integrating commit leaders. I have been using Git leaders for almost two years, but now I realize that I completely forgot about them.

  New Order, Power, Corruption & Lies.

Today was my first day at my new lab. Everything went fine, despite a very bad night. At least I have been able to go back home without too much dizziness or paresthesia in the legs (I don’t know where this one comes from). Guess what: For the first time in 10 years, I am able to connect my Macbook on the network! #self

I am reading the Racket guide again, this time using Dash only. It’s amazing how convenient this application is, especially for navigating between text and function definitions, which by default are all hyperlinked thanks to the Scribble documentation system. #scheme

  Nick Cave & The Bad Seeds, Push the Sky Away.

I am about to exceed the 150th micro-posts in my Org file. (Other posts are published from the terminal directly.) I added a little cookie to keep track of the number of entries, although a little harder path would be to write some elisp code. #org

I don’t have any big needs in terms of image processing, and I am generally happy with ImageMagick. However, Acorn and Retrobatch (h/t Brett Terpstra) look pretty nice.

  Nick Cave & The Bad Seeds, The Boatman’s Call.

Just cleanup a little bit more my Dropbox (6 Go of data, reports and papers accumulated along 8 years!).

Machine learning in Clojure with XGBoost. Note that there are bindings for the awesome xgboost in various other languages (Python, Julia, R), not just the JVM. #clojure

Python didn’t become the leader in the field because it’s inherently better or more performant, but because of scikit-learn, pandas and so on. While as Clojurists we don’t really need pandas (dataframes) or similar stuff (everything is just a map, or if you care more about memory and performance a record) we don’t have something like scikit-learn that makes really easy to train many kind of machine learning models and somewhat easier to deploy them.