All things related to IT, data, and programming that I come across and don't want to forget. The first things I would like to add to this repo are the things I don't do on a daily basis, because those are the things I am most likely to forget how to do.
The first way to divide up this information is between the tactical and the strategic
This is where we'll put the how-to's for specific programming languages and capture those languages' specific idioms. An example would be how all of the apply family functions work in R (lapply, sapply, tapply, mapply) or how list comprehension works in Python.
- Connecting R to a remote Oracle instance
- Plotting against maps in R (requiring a shapefile)
This is where we'll put generic concepts such as what is happening under the hood of a random forest algorithm. The focus is on the generic concept and not so much on the specific language being used (these will more than likely default to R until I have a new favorite language).
- Daileys: start with javascript and node
- R >> ggplot2 base plot font
- R >> incremented index id within groups (dplyr, data.table, ave)
- how this causes an issue with joins (do entire joins tutorial as well)
- how to use this for overall trend data, matching start events with end events
- R >> apply family functions
- R >> tranforming all values in a dataframe that fit a certain data type (isolate all numeric columns)
- R >> dplyr standard evals vs non standard evals examples (maybe with functions as well)
- Alexa >> Cutiemails deep dive (might not be exactly best practice, but is a good example of dynamodb interaction)
- R matrix -- need to learn different types of matrix operations, linear algebra, and different types / forms of sparse matrices