I have updated my development environment to a docker container running Ubuntu 22.04, with my usual 
suite of ML / Data ;ibraries pre-installed. I plan on adding jupyter notebook support in the future, as well as
the JAX library.

In addition, I need to figure out what, if anything, needs to stay consistent in a ML Docker project lifecycle.

A Snapshot from inside the Ubuntu Machine detailing some preinstalled libraries, including PyTorch and Transformers:
![Screen Shot 2023-03-30 at 3 38 27 AM](https://user-images.githubusercontent.com/62716243/228764187-4131b157-4c06-423f-855b-3e95acdaec88.png)


A screenshot of the Dockerfile:
<img width="607" alt="Screen Shot 2023-03-30 at 3 39 01 AM" src="https://user-images.githubusercontent.com/62716243/228764335-d228ee07-b935-411f-9483-601d85c61a63.png">