Reading

Recommended reading

Here are some suggested reading materials.

Do you wish to add your tutorial to this list? Do you have any suggestions for this list? - Let us talk!

Blogs #

• Squid’s Blogs by Carin Meier - deep learning, MXNet, Python interop and other technical topics

• Arthur Caillau’s Blog - featuring the “MXNet made simple” series

• Dragan Djuric - numerical computing, linear algebra, high performance computing and deep learning

• Christopher Small - discussing the development of Oz, among other things

• Clojure Goes Fast - overviews tools and practices for profiling and improving performance in Clojure

• Applied Science blog by Dave Liepmann, Matt Huebert and Jack Rusher - Deep learning, data visualization, data processing

Tutorials #

Tutorials play an important role on our journey to make Clojure an accessible, friendly platform for data science.

Of course, they allow us to share and learn existing methods and practices. No less importantly, working on tutorials helps us see the toolset meet its use cases, and thus realize what is still missing, and what could be improved.

General Nextjournal collections #

• Dieter Komentera - various topics

• Tomasz Sulej - various topics

• Alan Marazzi - various topics

• Carin Meier - mainly Python interop

• Chris Nuernberger - mainly Python interop

Math #

• Math for clojurists by Alan Marazzi

Data processing #

• techtest - comparing tech.ml.dataset with the analogous R packages - by Tomsaz Sulej

Transducers #

• A general introduction by Amit Ramon

Machine Learning #

XGBoost #

• clj-boost - A tutorial by Alan Marazzi

Python interop #

• See mainly the growing list of tutorials at Squid’s Blogs mentioned above.

Plotting #

• Fun With Matplotlib by Chris Nuernberger.
• Panthera tutorials

R interop #

• Clojisr tutorials
• Clojisr examples with lots of vizualiations, by Tomsaz Sulej and others

Literate programming #

• Clojupyter examples
• Notespace tutorial

Data Visualization #

• vdquil - Examples from Ben Fry’s “Visualizing Data” in quil - by Dave Liepmann

Books #

• Books by Dragan Djuric about Deep Learning and about Linear Algebra in Clojure - books developed alongside Dragan’s work on libraries in this fields

• Clojure for Data Science by Henry Garner - a bit dated in terms of the stack it presents, but stll relevant in terms of the principles presented

Other collections of resources #

• Resources for Clojure beginners collected by Dmitri Sotnikov