Use SMSL conda method for configuration

[wildintellect]

Sagemaker studio lab has a built in shortcut for quickly creating new conda environments as seen in https://github.com/aws/studio-lab-examples/blob/main/geospatial-data-science/NOAA_Exploratory_Analysis/EDA_weather_climate.ipynb

and described in https://github.com/aws/studio-lab-examples/tree/main/custom-environments

We should adopt this approach to keep each example isolated with it's own dependencies.

Acceptance criteria

• [x] Each example is it's own subfolder (can remove the redundant "example" folder)
• [x] Each example has a conda yml defining both conda installed libraries and pip required libraries when needed

[wildintellect]

Going to do this before #7 so that the conda yml can be used to pin versions.

[wildintellect]

We added conda yml for every notebook however without mamba the install via conda is painfully slow. For now, no plans to finish this until new conda/mamba is available in SMSL.

[wildintellect]

Just noting the correct syntax for using a yaml file to define a new conda env is: conda env create -n <name> --file env_dem.yml