/20190912-data-analytics-timeseries

Materials for the Conclusion & AMIS Machine Learning Guild - MeetUp on Data Analytics and Time Series

Primary LanguageJupyter Notebook

20190912-data-analytics-timeseries

Materials for the Conclusion & AMIS Machine Learning Guild - MeetUp on Data Analytics and Time Series

To get started on the workshop - go through these steps:

Run a command line shell on a Docker host

Execute this command to run a Jupyter Notebook (see https://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-scipy-notebook for more details on this Container Imgage that has Python 3.x, Anaconda, Pandas, Jupyter Lab, git)

docker run --name timeseries-data-analytics -d -p=8888:8888 jupyter/scipy-notebook

When the container is running, inspect its logs - and locate the Jupyter Lab token (after the line: The Jupyter Notebook is running at:) docker logs timeseries-data-analytics --follow

To complete setting up the container, please execute this command to open a shell session inside the container:

docker exec -it timeseries-data-analytics /bin/bash

then - inside the container - execute:

git clone https://github.com/AMIS-Services/20190912-data-analytics-timeseries

this clones a GitHub Repo that contains the notebook environment-setup. This notebook should be executed from the browser as a regular Jupyter Notebook. Then, open Notebook in the browser:

http://IP-Docker-Host:8888/notebooks/environment-setup.ipynb

and run the Notebook. This will install the required Python Libraries and the GitHub Repositories for the workshop.