Aylr / polyglotbook

polyglotbook

Audience

Working DS professionals that want to become polyglot. There is debate about the spectrum between DS and SWE.

Opinionated Pre-Requisites

• have used git
• can create data visualizations
• have written functions
• done ML

Focus

• narrative should follow a typical analytics/ML project from start to finish
• strong points of each language
• mechanics
• not intended to be comprehensive

TOC Ideas

1. Environments
   • conda
   • pip
   • virtualenv
   • docker
2. Handy Language Bits (I'm uncertain if this should be in "Gotchas")
   • how to access docstrings
   • interactive REPLS and autocomplete
   • R handy bits
     • ?function
     • function
     • function()
   • Python handy bits
3. Getting Data
   • csv
   • DBs
   • APIs
4. Gotchas / Internals
   • The good, the bad, and the ugly
   • scope
   • S3
   • OO
   • main
   • pass by value vs ...
   • variables
   • functions
   • classes
   • dispatch
   • inheritance
   • unit testing?
5. Analytics & Stats
6. Viz
7. Notebooks
8. ML
   • limited to tabular data on a single machine (in RAM)
9. Interfacing language
   • apache arrow, etc
10. Communicating / Telling Data Stories
11. Fun
    • packages
    • web apps
    • building APIs
    • interactive