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Introduction

Hands-on tutorial for machine learning

Prerequisites

  • Basic understanding of Machine Learning concepts
  • Basic Python knowledge
  • Basic Docker knowledge
  • Basic Jupyter knowledge
  • Docker installed
  • Approx. 1GB free disk space

Setup lab environment

Lab environment requires docker. To run the lab environment:

  • clone this repo
  • run docker
git clone https://github.com/hpe-container-platform-community/machine-learning-intro-tutorial.git
cd machine-learning-intro-tutorial
docker run -p 8888:8888 -v "$PWD":/home/jovyan jupyter/base-notebook

Note that the container folder /home/jovyan maps to the current folder, machine-learning-intro-tutorial.

Inspect the output for the URL, e.g.

...
[I 19:35:31.353 NotebookApp] Jupyter Notebook 6.1.4 is running at:
[I 19:35:31.353 NotebookApp] http://d8ce476914a2:8888/?token=d7c9f2df7c0f369dcdacc114cac6f8897e1e0987a1a5e275
[I 19:35:31.353 NotebookApp]  or http://127.0.0.1:8888/?token=d7c9f2df7c0f369dcdacc114cac6f8897e1e0987a1a5e275

Open the URL (for me this was: http://127.0.0.1:8888/?token=d7c9f2df7c0f369dcdacc114cac6f8897e1e0987a1a5e275)

NOTE: You will get a different URL every time you run the docker instance.

Tutorials

After running the lab environment you can open the tutorials in the UI and follow the instructions.